Triple
T38378313
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chaghasarai |
E893685
|
entity |
| Predicate | hasCapitalRoleInPast |
P18085
|
FINISHED |
| Object | Asadabad County |
—
|
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: Asadabad County | Statement: [Chaghasarai, hasCapitalRoleInPast, Asadabad County]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCapitalRoleInPast Context triple: [Chaghasarai, hasCapitalRoleInPast, Asadabad County]
-
A.
hasHistoricalRoleAs
Indicates that an entity has served in a specific historical capacity, function, or position during a particular period or context.
-
B.
hasCapitalRole
chosen
Indicates that an entity holds an official role, function, or status specifically associated with a capital city.
-
C.
mayHavePriorRole
Indicates that an entity is allowed or expected to have held a specified role at some earlier time.
-
D.
hasNotableFormerMemberRole
Indicates that an entity has a role or position that was notably held by a former member of that entity.
-
E.
hasNamesakePositionHeld
Indicates that one entity has held a position or office that is also held (or was held) by another entity with the same name.
- 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_69f76e4b1f748190a380696a16eae4a2 |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_6a0064f8efa48190956287f548a8057d |
completed | May 10, 2026, 10:59 a.m. |
| PD | Predicate disambiguation | batch_6a006471e75c8190adae99bd75e7411b |
completed | May 10, 2026, 10:56 a.m. |
Created at: May 3, 2026, 4:31 p.m.