Triple
T6326811
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | HON |
E141881
|
entity |
| Predicate | primaryBusinessArea |
P70059
|
FINISHED |
| Object | aerospace |
—
|
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: aerospace | Statement: [HON, primaryBusinessArea, aerospace]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: primaryBusinessArea Context triple: [HON, primaryBusinessArea, aerospace]
-
A.
primaryArea
Indicates that one entity is the main or most important area, domain, or field associated with another entity.
-
B.
notableRegionOfBusiness
Indicates that a specified geographic region is a significant or primary area in which an entity conducts its business activities.
-
C.
primaryTrade
Indicates that the referenced activity or exchange is the main or most significant trade relationship associated with the entities involved.
-
D.
laterMainBusiness
Indicates that one business activity or enterprise occurs after and succeeds another as the main business.
-
E.
primaryWork
Indicates that one work is the main or most significant work associated with a given entity, as opposed to other secondary or related works.
- F. None of above. chosen
Provenance (4 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_69c008d201748190917e69c41ba3f978 |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c064e833a0819096000b47e776949d |
completed | March 22, 2026, 9:53 p.m. |
| PD | Predicate disambiguation | batch_69c060e5efc48190861b8266e5b0cc0c |
completed | March 22, 2026, 9:36 p.m. |
| PDg | Predicate description generation | batch_69c0623bb29081908bfdfb84a07ece90 |
completed | March 22, 2026, 9:42 p.m. |
Created at: March 22, 2026, 4:29 p.m.