Triple
T2221770
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kadima |
E48155
|
entity |
| Predicate | servedInRole |
P37119
|
FINISHED |
| Object | ruling party of Israel |
—
|
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: ruling party of Israel | Statement: [Kadima, servedInRole, ruling party of Israel]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: servedInRole Context triple: [Kadima, servedInRole, ruling party of Israel]
-
A.
servedAs
Indicates that one entity held and performed the role, position, or function associated with another entity for some period of time.
-
B.
servedInCabinetOf
Indicates that one person held a position as a member of the governmental cabinet led by another person.
-
C.
militaryRole
Indicates the specific function, position, or duty an entity holds within a military organization or context.
-
D.
alsoServedAs
Indicates that an entity held an additional role or position beyond the primary one already mentioned.
-
E.
hasHistoricalRoleAs
Indicates that an entity has served in a specific historical capacity, function, or position during a particular period or context.
- 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_69a88aa1ee708190862c8c378c41e9eb |
completed | March 4, 2026, 7:40 p.m. |
| NER | Named-entity recognition | batch_69abc03bfdd48190bfb96ec3e41c22dc |
completed | March 7, 2026, 6:05 a.m. |
| PD | Predicate disambiguation | batch_69abbdac31d8819092d17815e11921e9 |
completed | March 7, 2026, 5:54 a.m. |
| PDg | Predicate description generation | batch_69abbfe93d7c81909f1b9c1b1e3c7989 |
completed | March 7, 2026, 6:04 a.m. |
Created at: March 4, 2026, 7:47 p.m.