Triple
T6884550
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Agnes Ayres |
E158883
|
entity |
| Predicate | spouse |
P13
|
FINISHED |
| Object |
Manuel Reachi
Manuel Reachi was a film producer and industry figure best known for his marriage to silent film actress Agnes Ayres.
|
E689698
|
NE FINISHED |
How this triple was built (4 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Manuel Reachi | Statement: [Agnes Ayres, spouse, Manuel Reachi]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Manuel Reachi Context triple: [Agnes Ayres, spouse, Manuel Reachi]
-
A.
Manuel Vega
Manuel Vega is a designer best known for his work on the Moonman character.
-
B.
Manuel Medina
Manuel Medina is a Mexican former professional boxer and multiple-time featherweight world champion known for his technical skill and durability in the ring.
-
C.
Manuel Salgado
Manuel Salgado is a Portuguese architect best known for his influential public and cultural building designs, including major projects in Lisbon.
-
D.
Arturo Chávez
Arturo Chávez is a personal name that may refer to multiple individuals, including professionals and public figures in Spanish-speaking countries.
-
E.
Manuel Serrano
Manuel Serrano is a computer scientist and software engineer best known for creating and maintaining the Bigloo Scheme compiler and contributing to programming language implementation and web programming tools.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Manuel Reachi Triple: [Agnes Ayres, spouse, Manuel Reachi]
Generated description
Manuel Reachi was a film producer and industry figure best known for his marriage to silent film actress Agnes Ayres.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Manuel Reachi Target entity description: Manuel Reachi was a film producer and industry figure best known for his marriage to silent film actress Agnes Ayres.
-
A.
Manuel Vega
Manuel Vega is a designer best known for his work on the Moonman character.
-
B.
Manuel Medina
Manuel Medina is a Mexican former professional boxer and multiple-time featherweight world champion known for his technical skill and durability in the ring.
-
C.
Manuel Salgado
Manuel Salgado is a Portuguese architect best known for his influential public and cultural building designs, including major projects in Lisbon.
-
D.
Arturo Chávez
Arturo Chávez is a personal name that may refer to multiple individuals, including professionals and public figures in Spanish-speaking countries.
-
E.
Manuel Serrano
Manuel Serrano is a computer scientist and software engineer best known for creating and maintaining the Bigloo Scheme compiler and contributing to programming language implementation and web programming tools.
- F. None of above. chosen
Provenance (5 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69c688342f6c8190ad7eea6ba262db99 |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6d90a2590819092ff253dd66ebe8b |
completed | March 27, 2026, 7:22 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c9061709f48190a9e198dac225aed4 |
completed | March 29, 2026, 10:59 a.m. |
| NEDg | Description generation | batch_69c9069a60e88190be4b8c1dc1f1a3af |
completed | March 29, 2026, 11:01 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69c9071da2c48190b3d50e460c312c67 |
completed | March 29, 2026, 11:03 a.m. |
Created at: March 27, 2026, 2:23 p.m.