Triple
T10017289
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Irish in the Middle East |
E199525
|
entity |
| Predicate | sectorOfEmployment |
P62124
|
FINISHED |
| Object | construction |
—
|
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: construction | Statement: [Irish in the Middle East, sectorOfEmployment, construction]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: sectorOfEmployment Context triple: [Irish in the Middle East, sectorOfEmployment, construction]
-
A.
hasOccupationSector
Indicates that an entity’s occupation belongs to or is categorized within a particular economic or professional sector.
-
B.
ownerSector
Indicates the sector or industry category to which the owner of an entity belongs.
-
C.
occupationType
Indicates the specific kind or category of work, profession, or role that an entity performs or holds.
-
D.
professionalSector
chosen
Indicates the industry or field in which an entity conducts its professional or occupational activities.
-
E.
employmentType
Indicates the specific kind or category of employment relationship that exists between an individual and an employer (e.g., full-time, part-time, contract).
- 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_69ca8315a1a08190ab310f25620f362b |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cdcd4c17848190bf1a8017e755ba75 |
completed | April 2, 2026, 1:58 a.m. |
| PD | Predicate disambiguation | batch_69cd4b7cd4208190b2253583ee2f892c |
completed | April 1, 2026, 4:44 p.m. |
Created at: March 30, 2026, 8:53 p.m.