Triple
T34332379
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nizamabad Lok Sabha constituency |
E881049
|
entity |
| Predicate | predecessorStateUnit |
P10077
|
FINISHED |
| Object | Hyderabad State |
—
|
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: Hyderabad State | Statement: [Nizamabad Lok Sabha constituency, predecessorStateUnit, Hyderabad State]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: predecessorStateUnit Context triple: [Nizamabad Lok Sabha constituency, predecessorStateUnit, Hyderabad State]
-
A.
predecessorState
chosen
Indicates that one state directly precedes another in a sequence or process.
-
B.
predecessorUnit
Indicates that one unit directly precedes another in an ordered sequence or hierarchy.
-
C.
predecessorStateOf
Indicates that one state occurs immediately before and leads into another state in a sequence or process.
-
D.
predecessorStateContext
Indicates that one state serves as the immediately preceding state within a given contextual sequence or process.
-
E.
predecessorStateForm
Indicates that one state form directly precedes another in a temporal or historical sequence.
- 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_69f349ba96a08190b94887bae2d8ee49 |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_69fd884cb2b48190b6acd473430d9e19 |
completed | May 8, 2026, 6:53 a.m. |
| PD | Predicate disambiguation | batch_69fd8709ca208190a8bab836f0156af5 |
completed | May 8, 2026, 6:47 a.m. |
Created at: May 1, 2026, 1:58 a.m.