Triple
T19502081
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Guido Crosetto |
E487927
|
entity |
| Predicate | hasWorkedInSector |
P62538
|
FINISHED |
| Object | defence industry |
—
|
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: defence industry | Statement: [Guido Crosetto, hasWorkedInSector, defence industry]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasWorkedInSector Context triple: [Guido Crosetto, hasWorkedInSector, defence industry]
-
A.
hasWorkedIn
Indicates that a person has been employed or has performed work within a particular organization, location, or domain for some period of time.
-
B.
hasOccupationSector
chosen
Indicates that an entity’s occupation belongs to or is categorized within a particular economic or professional sector.
-
C.
hasWorkedFor
Indicates that an entity has been employed by or has provided work or services to another entity.
-
D.
hasIndustryRole
Indicates that an entity holds or performs a specific role, function, or position within a particular industry or sector.
-
E.
hasWorksIn
Indicates that one entity is employed by or performs their professional activities within the organization, location, or context represented by another entity.
- 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_69d8e8d9d1c88190b01cd78b8be49384 |
completed | April 10, 2026, 12:11 p.m. |
| NER | Named-entity recognition | batch_69e6350dbae08190bea7fc3e3eb95c3c |
completed | April 20, 2026, 2:15 p.m. |
| PD | Predicate disambiguation | batch_69e4fd7bd25881908caa04eaef1f6718 |
completed | April 19, 2026, 4:06 p.m. |
Created at: April 10, 2026, 1:40 p.m.