Triple
T21236557
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Luc Demers |
E523358
|
entity |
| Predicate | hasGivenName |
P17
|
FINISHED |
| Object |
Luc
Luc is a masculine given name of French origin, commonly used in Francophone countries and equivalent to the English name Luke.
|
E216416
|
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: Luc | Statement: [Luc Demers, hasGivenName, Luc]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Luc Context triple: [Luc Demers, hasGivenName, Luc]
-
A.
Luc
Luc is the given name of Luc Longley, the Australian former professional basketball player and three-time NBA champion with the Chicago Bulls.
-
B.
Lou
Lou is a supporting character in the romantic drama film "Stuck in Love," involved in the intertwined relationships and personal struggles of a family of writers.
-
C.
Lou
Lou is the central canine hero of the animated film "Cats & Dogs," leading the fight to protect humanity from a secret feline plot.
-
D.
Lou
Lou is a character in the television miniseries "The Continental: From the World of John Wick," set in the action-packed criminal underworld of the John Wick franchise.
-
E.
Lou
Lou is a character in the crime thriller film "Deadfall," involved in the movie’s tense, violent family-centered plot.
- 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: Luc Triple: [Luc Demers, hasGivenName, Luc]
Generated description
Luc is a masculine given name of French origin, commonly used in Francophone countries and equivalent to the English name Luke.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Luc Target entity description: Luc is a masculine given name of French origin, commonly used in Francophone countries and equivalent to the English name Luke.
-
A.
Luc
chosen
Luc is the given name of Luc Longley, the Australian former professional basketball player and three-time NBA champion with the Chicago Bulls.
-
B.
Lou
Lou is a supporting character in the romantic drama film "Stuck in Love," involved in the intertwined relationships and personal struggles of a family of writers.
-
C.
Lou
Lou is a character in the crime thriller film "Deadfall," involved in the movie’s tense, violent family-centered plot.
-
D.
Lou
Lou is the central canine hero of the animated film "Cats & Dogs," leading the fight to protect humanity from a secret feline plot.
-
E.
Lou
Lou is a character in the television miniseries "The Continental: From the World of John Wick," set in the action-packed criminal underworld of the John Wick franchise.
- F. None of above.
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_69e0b513b89c81908b27147e91368db2 |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e735202c7481909c642ddaafb40671 |
completed | April 21, 2026, 8:28 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0986f0015c8190aa854cc91a87f7e6 |
completed | May 17, 2026, 9:14 a.m. |
| NEDg | Description generation | batch_6a0987a9ceac819083ecb7988661235a |
completed | May 17, 2026, 9:17 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a09881c2d4c8190ab2cdf5dc99a43b0 |
completed | May 17, 2026, 9:19 a.m. |
Created at: April 16, 2026, 3:46 p.m.