Triple
T150196
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gabriel García Márquez |
E3414
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Gabriel |
E8490
|
NE FINISHED |
How this triple was built (2 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: Gabriel | Statement: [Gabriel García Márquez, givenName, Gabriel]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Gabriel Context triple: [Gabriel García Márquez, givenName, Gabriel]
-
A.
Gabriel
chosen
Gabriel is a common masculine given name of Hebrew origin, widely used in many cultures and languages.
-
B.
Degory Priest
Degory Priest was an English Pilgrim and early settler of Plymouth Colony who traveled on the Mayflower and participated in the founding governance of the colony.
-
C.
Timothy
Timothy is the given first name of Sir Tim Berners-Lee, the British computer scientist who invented the World Wide Web.
-
D.
Jerome
Jerome was an early Christian scholar and theologian best known for translating the Bible into Latin (the Vulgate) and for his influential biblical commentaries.
-
E.
Tiago
Tiago is a masculine given name commonly used in Portuguese-speaking countries, often considered a variant of the name James.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69a252868de4819080e21c9938bfe8b6 |
completed | Feb. 28, 2026, 2:27 a.m. |
| NER | Named-entity recognition | batch_69a2580dda148190a522e0ac276d5f33 |
completed | Feb. 28, 2026, 2:50 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a31c8fe0ec81908e96c597c5f949b7 |
completed | Feb. 28, 2026, 4:49 p.m. |
Created at: Feb. 28, 2026, 2:31 a.m.