Triple
T37674104
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Defense Minister of Israel |
E938042
|
entity |
| Predicate | hasHadNotableOfficeHolder |
P67246
|
FINISHED |
| Object | David Ben-Gurion |
—
|
NE NERFINISHED |
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: David Ben-Gurion | Statement: [Defense Minister of Israel, hasHadNotableOfficeHolder, David Ben-Gurion]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasHadNotableOfficeHolder Context triple: [Defense Minister of Israel, hasHadNotableOfficeHolder, David Ben-Gurion]
-
A.
hasHistoricalOfficeHolder
chosen
Indicates that an office, position, or role has been held by a specific person at some point in the past.
-
B.
hasFirstOfficeholder
Indicates that a position, role, or office is associated with the person or entity who first held it.
-
C.
hasMemberWhoHeldOffice
Indicates that a group or organization includes at least one member who has held a specified office or position.
-
D.
hasListOfOfficeHolders
Indicates that an entity is associated with a collection or record enumerating the individuals who have held a particular office or position.
-
E.
hasLeaderHeldOffice
Indicates that the specified leader has occupied or served in an official office or position.
- 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_69f76ed7b1408190ba8c93c53cb8becf |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69fbb9e8108c8190ae1c7940b1677e95 |
completed | May 6, 2026, 10 p.m. |
| PD | Predicate disambiguation | batch_69fbb141605c8190b9c27d70352522db |
completed | May 6, 2026, 9:23 p.m. |
Created at: May 3, 2026, 4:18 p.m.