Triple
T29338764
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | State Disaster Response Forces |
E743979
|
entity |
| Predicate | hasUnitIn |
P178603
|
FINISHED |
| Object | Andhra Pradesh |
—
|
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: Andhra Pradesh | Statement: [State Disaster Response Forces, hasUnitIn, Andhra Pradesh]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasUnitIn Context triple: [State Disaster Response Forces, hasUnitIn, Andhra Pradesh]
-
A.
hasUnitOf
Indicates that a quantity, measurement, or value is expressed in terms of a specific unit.
-
B.
isUnitIn
Indicates that a specific unit is located within or belongs to a particular container, group, or context.
-
C.
hasUnitFeature
Indicates that something possesses a specific unit-related characteristic or attribute, such as a measurable feature expressed in defined units.
-
D.
mayHaveUnit
Indicates that an entity can optionally be associated with a specific unit of measurement.
-
E.
isAUnitOf
Indicates that one entity functions as a unit or standard measure in which the other entity is quantified or expressed.
- 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_69f09126cfcc8190899b16fbf3c2bf7b |
completed | April 28, 2026, 10:51 a.m. |
| NER | Named-entity recognition | batch_69f7117e55908190a67105e92bc4830f |
completed | May 3, 2026, 9:12 a.m. |
| PD | Predicate disambiguation | batch_69f70f380690819090cc34763ba460ed |
completed | May 3, 2026, 9:02 a.m. |
| PDg | Predicate description generation | batch_69f7117cf2188190b29e36fc1e342c60 |
completed | May 3, 2026, 9:12 a.m. |
Created at: April 28, 2026, 1:32 p.m.