Triple
T1292535
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Professional Products Division |
E27577
|
entity |
| Predicate | segmentOf |
P17710
|
FINISHED |
| Object | L'Oréal professional products segment |
—
|
LITERAL 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: L'Oréal professional products segment | Statement: [Professional Products Division, segmentOf, L'Oréal professional products segment]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: segmentOf Context triple: [Professional Products Division, segmentOf, L'Oréal professional products segment]
-
A.
subrange
Indicates that one value or interval lies entirely within the bounds of another value or interval.
-
B.
operatesInSegment
Indicates that an entity conducts its activities or provides its services within a specified market or operational segment.
-
C.
formsInitialSegmentOf
Indicates that one entity constitutes the starting portion or beginning segment of another, larger entity or sequence.
-
D.
segmentStructure
chosen
Indicates that one entity represents a structural or organizational subdivision (a segment) within the overall structure of another entity.
-
E.
locatedBetween
Indicates that one entity is positioned spatially between two other reference entities.
- 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_69a496d4ec448190ad653b2590c46711 |
completed | March 1, 2026, 7:43 p.m. |
| NER | Named-entity recognition | batch_69a4c3bb3a9c81909db2ad91defd87b6 |
completed | March 1, 2026, 10:54 p.m. |
| PD | Predicate disambiguation | batch_69a4bee64d908190b6a9bb479959d523 |
completed | March 1, 2026, 10:34 p.m. |
Created at: March 1, 2026, 7:51 p.m.