Triple
T9418925
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Glynn Turman |
E227100
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object |
Turman
Turman is the surname of American actor Glynn Turman, known for his extensive work in film, television, and theater.
|
E798359
|
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: Turman | Statement: [Glynn Turman, familyName, Turman]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Turman Context triple: [Glynn Turman, familyName, Turman]
-
A.
Tura
Tura is a prominent town in the Indian state of Meghalaya, serving as a major administrative, cultural, and economic center in the Garo Hills region.
-
B.
Tura
Tura is a district in southern Cairo, Egypt, historically known for its limestone quarries used in ancient Egyptian monuments.
-
C.
Buir
Buir is a district or locality within the town of Kerpen in North Rhine-Westphalia, Germany.
-
D.
Blizne
Blizne is a village in southeastern Poland best known for its historic wooden All Saints Church, a UNESCO World Heritage Site.
-
E.
Tarusa
Tarusa is a small historic town in western Russia known for its scenic location on the Oka River and its associations with Russian artists and writers.
- 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: Turman Triple: [Glynn Turman, familyName, Turman]
Generated description
Turman is the surname of American actor Glynn Turman, known for his extensive work in film, television, and theater.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Turman Target entity description: Turman is the surname of American actor Glynn Turman, known for his extensive work in film, television, and theater.
-
A.
Tura
Tura is a prominent town in the Indian state of Meghalaya, serving as a major administrative, cultural, and economic center in the Garo Hills region.
-
B.
Tura
Tura is a district in southern Cairo, Egypt, historically known for its limestone quarries used in ancient Egyptian monuments.
-
C.
Buir
Buir is a district or locality within the town of Kerpen in North Rhine-Westphalia, Germany.
-
D.
Blizne
Blizne is a village in southeastern Poland best known for its historic wooden All Saints Church, a UNESCO World Heritage Site.
-
E.
Tarusa
Tarusa is a small historic town in western Russia known for its scenic location on the Oka River and its associations with Russian artists and writers.
- 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_69ca84359e7c819091148ba4b670e436 |
completed | March 30, 2026, 2:09 p.m. |
| NER | Named-entity recognition | batch_69cd68cd1e3481909abcb715e2398120 |
completed | April 1, 2026, 6:49 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d107c4d73881909ac38781fe90b1da |
completed | April 4, 2026, 12:44 p.m. |
| NEDg | Description generation | batch_69d1085a980c8190b4c6d811b07ab180 |
completed | April 4, 2026, 12:47 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69d1093f440481909aa27287019191ac |
completed | April 4, 2026, 12:51 p.m. |
Created at: March 30, 2026, 7:48 p.m.