Triple
T1477270
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dadra and Nagar Haveli and Daman and Diu |
E30869
|
entity |
| Predicate | isNonContiguous |
P29207
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Dadra and Nagar Haveli and Daman and Diu, isNonContiguous, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isNonContiguous Context triple: [Dadra and Nagar Haveli and Daman and Diu, isNonContiguous, true]
-
A.
isContiguousState
Indicates that a state shares a continuous land border with the main body of the country, without being separated by foreign territory or significant bodies of water.
-
B.
isNonzeroFor
Indicates that a given value, function, or quantity is not equal to zero under specified conditions or for specified inputs.
-
C.
areDisjointWith
Indicates that two entities have no elements, instances, or members in common within the specified context.
-
D.
isNonBinding
Indicates that the relationship or agreement exists but does not create any legally or formally enforceable obligation between the involved entities.
-
E.
isComposite
Indicates that an entity is made up of multiple components or parts combined into a single whole.
- 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_69a498fe55a88190ab7f9e40ace88e49 |
completed | March 1, 2026, 7:52 p.m. |
| NER | Named-entity recognition | batch_69a4c603f9e88190b340734709534860 |
completed | March 1, 2026, 11:04 p.m. |
| PD | Predicate disambiguation | batch_69a4c484e52c81908948ff8c0a42751b |
completed | March 1, 2026, 10:58 p.m. |
| PDg | Predicate description generation | batch_69a4c57984088190b2c2d2d9cc2e5df9 |
completed | March 1, 2026, 11:02 p.m. |
Created at: March 1, 2026, 8:11 p.m.