Triple
T13538138
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Arkema |
E323313
|
entity |
| Predicate | hasSubsidiary |
P254
|
FINISHED |
| Object | Bostik |
E88625
|
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: Bostik | Statement: [Arkema, hasSubsidiary, Bostik]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bostik Context triple: [Arkema, hasSubsidiary, Bostik]
-
A.
Bondo
Bondo is a town in western Kenya’s Nyanza region, known as an administrative and commercial center near Lake Victoria.
-
B.
Viewliner
Viewliner is a class of single-level passenger railcars used primarily by Amtrak for long-distance overnight service in the United States.
-
C.
Glue
"Glue" is a novel by Scottish author Irvine Welsh that follows the intertwined lives of four working-class friends in Edinburgh over several decades.
-
D.
LouSeal
LouSeal is the playful seal mascot of the Columbus Clippers minor league baseball team, entertaining fans at games in Columbus, Ohio.
-
E.
Elmer's
chosen
Elmer's is a well-known American brand best recognized for its school and craft glues and other adhesive products.
- 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_69d8076776248190bdf0d4fa1f85a5fc |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dbafbe39948190808062d4eff91841 |
completed | April 12, 2026, 2:44 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f75d9c04b881908a359df791b89b43 |
completed | May 3, 2026, 2:37 p.m. |
Created at: April 9, 2026, 9:45 p.m.