Triple
T4400620
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Moradabad |
E93604
|
entity |
| Predicate | demographicsCategory |
P2263
|
FINISHED |
| Object | city in Uttar Pradesh |
—
|
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: city in Uttar Pradesh | Statement: [Moradabad, demographicsCategory, city in Uttar Pradesh]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: demographicsCategory Context triple: [Moradabad, demographicsCategory, city in Uttar Pradesh]
-
A.
demographics
Indicates the relationship of providing or characterizing statistical information about a population’s attributes, such as age, gender, income, or education.
-
B.
demographicsLabel
chosen
Indicates the categorical demographic group or segment that an entity is associated with or classified under.
-
C.
demographicsDescriptor
Indicates a descriptive attribute or classification that characterizes the demographic properties of an entity or group.
-
D.
demographicsCharacteristic
Indicates that one entity serves as a demographic attribute or characteristic (such as age, gender, ethnicity, etc.) that describes or classifies another entity.
-
E.
demographicCharacteristic
Indicates that one entity specifies or describes a demographic attribute or feature (such as age, gender, ethnicity, or similar population-related trait) of another entity.
- 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_69b345158c748190a2c040fce2da9980 |
completed | March 12, 2026, 10:58 p.m. |
| NER | Named-entity recognition | batch_69b352cd71ec8190a62320fd072f744f |
completed | March 12, 2026, 11:57 p.m. |
| PD | Predicate disambiguation | batch_69b34f597998819092477efdedb51427 |
completed | March 12, 2026, 11:42 p.m. |
Created at: March 12, 2026, 11:28 p.m.