Triple
T23875569
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tamba region |
E592854
|
entity |
| Predicate | historicalProvinceSuccessorOf |
P123680
|
FINISHED |
| Object | Tanba Province |
—
|
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: Tanba Province | Statement: [Tamba region, historicalProvinceSuccessorOf, Tanba Province]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: historicalProvinceSuccessorOf Context triple: [Tamba region, historicalProvinceSuccessorOf, Tanba Province]
-
A.
historicalRegionSuccessor
Indicates that one historical region directly follows and replaces another in terms of territorial or administrative continuity.
-
B.
historicalProvinceGroup
Indicates that two or more provinces are grouped together based on sharing a common historical administrative or territorial affiliation.
-
C.
formerProvince
Indicates that an entity was previously a province of another entity but no longer holds that administrative status.
-
D.
successorProvinceOrState
chosen
Indicates that one province or state has officially replaced or continued the role of another as its successor.
-
E.
laterProvinceName
Indicates that an entity (such as a region or administrative unit) is known by a different province name at a later point in time.
- 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_69e25d23a5c88190ae3999c70ca15e08 |
completed | April 17, 2026, 4:17 p.m. |
| NER | Named-entity recognition | batch_69f1cc012974819090b34aad6a230f81 |
completed | April 29, 2026, 9:14 a.m. |
| PD | Predicate disambiguation | batch_69f1614a65a88190bde1efb368a151e4 |
completed | April 29, 2026, 1:39 a.m. |
Created at: April 17, 2026, 8:15 p.m.