Triple
T38235451
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Baccarat |
E1013607
|
entity |
| Predicate | hasArtisanWorkforce |
P104132
|
FINISHED |
| Object | master glassmakers |
—
|
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: master glassmakers | Statement: [Baccarat, hasArtisanWorkforce, master glassmakers]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasArtisanWorkforce Context triple: [Baccarat, hasArtisanWorkforce, master glassmakers]
-
A.
hasWorkforceType
Indicates the type or category of workforce associated with an entity (such as permanent, temporary, contract, or part-time).
-
B.
hasCraftsman
Indicates that one entity serves as the craftsman, maker, or artisan responsible for creating, building, or crafting another entity.
-
C.
hasArtisanActivity
chosen
Indicates that an entity engages in or is associated with a specific craft or artisan-related activity.
-
D.
hasCivilianWorkforce
Indicates that an entity employs or is associated with a group of civilian (non-military) workers.
-
E.
hasEmployees
Indicates that one entity employs one or more other entities as its workers or staff.
- 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_69f76dd72a248190a5fe18db2bd1eb15 |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69feb5e66224819083b87c3707a5a5e0 |
completed | May 9, 2026, 4:19 a.m. |
| PD | Predicate disambiguation | batch_69feb3bd700c8190991ed200cd3c04db |
completed | May 9, 2026, 4:10 a.m. |
Created at: May 3, 2026, 4:30 p.m.