Triple
T34184007
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lou Laurin-Lam |
E876904
|
entity |
| Predicate | worksOnSubject |
P7040
|
FINISHED |
| Object | Wifredo Lam |
—
|
NE NERFINISHED |
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: Wifredo Lam | Statement: [Lou Laurin-Lam, worksOnSubject, Wifredo Lam]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: worksOnSubject Context triple: [Lou Laurin-Lam, worksOnSubject, Wifredo Lam]
-
A.
worksAgainst
Indicates that one entity actively opposes, counteracts, or undermines the goals, effects, or interests of another entity.
-
B.
worksFor
Indicates that one entity is employed by or performs work on behalf of another entity, typically an organization or individual.
-
C.
worksTo
Indicates that one entity performs work or exerts effort in order to achieve, support, or contribute to another entity or outcome.
-
D.
worksOnProgram
Indicates that an entity is actively involved in contributing effort or performing tasks on a particular program.
-
E.
subjectOfWork
chosen
Indicates that one entity is the main topic, focus, or theme that a particular work (such as a book, article, or artwork) is about.
- F. None of above.
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_69f349ae640c8190b9cd220b5368d8b6 |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_69fb6fdc7eb081908ab8475efb38c430 |
completed | May 6, 2026, 4:44 p.m. |
| PD | Predicate disambiguation | batch_69fb5a986e588190b7a10892bd2ff44c |
completed | May 6, 2026, 3:13 p.m. |
Created at: May 1, 2026, 1:55 a.m.