Triple
T19905397
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lemaire |
E478399
|
entity |
| Predicate | hasNotableBearer |
P458
|
FINISHED |
| Object |
Louis Lemaire
Louis Lemaire is a relatively obscure individual known primarily for sharing the Lemaire surname rather than for widely recognized achievements.
|
E1402734
|
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: Louis Lemaire | Statement: [Lemaire, hasNotableBearer, Louis Lemaire]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Louis Lemaire Context triple: [Lemaire, hasNotableBearer, Louis Lemaire]
-
A.
Auguste‑Henri Lemaire
Auguste‑Henri Lemaire was a 19th‑century French sculptor known for his work on prominent Parisian monuments.
-
B.
Philippe Joseph Henri Lemaire
Philippe Joseph Henri Lemaire was a 19th-century French sculptor known for his religious and architectural works in Paris.
-
C.
Louis Justement
Louis Justement was an American architect known for his influential mid-20th-century designs in Washington, D.C., including major federal and civic buildings.
-
D.
Eric Lassard
Eric Lassard is the bumbling yet kind-hearted and eccentric commandant of the police academy in the Police Academy comedy film series.
-
E.
Alain Chevalier
Alain Chevalier was a French businessman best known as a co-founder and early architect of the luxury goods conglomerate LVMH.
- 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: Louis Lemaire Triple: [Lemaire, hasNotableBearer, Louis Lemaire]
Generated description
Louis Lemaire is a relatively obscure individual known primarily for sharing the Lemaire surname rather than for widely recognized achievements.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Louis Lemaire Target entity description: Louis Lemaire is a relatively obscure individual known primarily for sharing the Lemaire surname rather than for widely recognized achievements.
-
A.
Auguste‑Henri Lemaire
Auguste‑Henri Lemaire was a 19th‑century French sculptor known for his work on prominent Parisian monuments.
-
B.
Philippe Joseph Henri Lemaire
Philippe Joseph Henri Lemaire was a 19th-century French sculptor known for his religious and architectural works in Paris.
-
C.
Louis Justement
Louis Justement was an American architect known for his influential mid-20th-century designs in Washington, D.C., including major federal and civic buildings.
-
D.
Eric Lassard
Eric Lassard is the bumbling yet kind-hearted and eccentric commandant of the police academy in the Police Academy comedy film series.
-
E.
Alain Chevalier
Alain Chevalier was a French businessman best known as a co-founder and early architect of the luxury goods conglomerate LVMH.
- 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_69d8e520682081909892916424699bd5 |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e65945cc2081908224902d5f042d7a |
completed | April 20, 2026, 4:50 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a07f6dbed3c8190abba458865896766 |
completed | May 16, 2026, 4:47 a.m. |
| NEDg | Description generation | batch_6a07f83250fc8190bdcf86f1981e47f6 |
completed | May 16, 2026, 4:53 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a07f8c025488190bdc06977f07e6ddc |
completed | May 16, 2026, 4:55 a.m. |
Created at: April 10, 2026, 1:52 p.m.