Triple
T27718170
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dam |
E698875
|
entity |
| Predicate | hasOccupationalAssociation |
P75202
|
FINISHED |
| Object | architects |
—
|
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: architects | Statement: [Dam, hasOccupationalAssociation, architects]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasOccupationalAssociation Context triple: [Dam, hasOccupationalAssociation, architects]
-
A.
occupationalAssociation
chosen
Indicates a relationship where one entity is connected to another through a job, profession, or work-related role.
-
B.
hasCloseProfessionalAssociationWith
Indicates a strong, ongoing professional relationship or collaboration between two entities, typically involving frequent interaction or shared work responsibilities.
-
C.
isOccupationalFormOf
Indicates that one occupation is a specific form, variant, or specialization of another, more general occupation.
-
D.
isAssociatedWithProfessionOfBearer
Indicates that one entity is connected to, or involved with, the profession or occupational role held by another entity.
-
E.
hasProfessionalRelationshipWith
Indicates a formal, work-related connection or collaboration exists between the two entities in a professional context.
- 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_69ef591012dc8190a6f1ec994f9f7ff7 |
completed | April 27, 2026, 12:39 p.m. |
| NER | Named-entity recognition | batch_69f63639a84c81909d700a539b458b42 |
completed | May 2, 2026, 5:36 p.m. |
| PD | Predicate disambiguation | batch_69f62c1a92648190835a2c5250d8c758 |
completed | May 2, 2026, 4:53 p.m. |
Created at: April 27, 2026, 3:05 p.m.