Triple
T33643468
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Inderpuri |
E861893
|
entity |
| Predicate | hasPINCodeArea |
P177458
|
FINISHED |
| Object | Pusa Road – Inderpuri area |
—
|
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: Pusa Road – Inderpuri area | Statement: [Inderpuri, hasPINCodeArea, Pusa Road – Inderpuri area]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPINCodeArea Context triple: [Inderpuri, hasPINCodeArea, Pusa Road – Inderpuri area]
-
A.
hasPINCode
Indicates that an entity is associated with or assigned a specific personal identification number (PIN) code.
-
B.
hasPINCodeSystem
Indicates that an entity is equipped with or uses a PIN code–based authentication or access control system.
-
C.
hasAreaCode
Indicates that a specified telephone area code is assigned to or associated with a particular geographic region, location, or phone service entity.
-
D.
hasPin
Indicates that one entity possesses, includes, or is equipped with a specific pin (such as a connector pin, security PIN, or fastening pin).
-
E.
hasAreaNumber
Indicates that an entity is associated with a specific area identified by a numerical code.
- 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_69f3498280c48190bcc3494017d14234 |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69f6fb93224881908fc66fe76115fcdb |
completed | May 3, 2026, 7:38 a.m. |
| PD | Predicate disambiguation | batch_69f6f96badb08190994442c2aba840b1 |
completed | May 3, 2026, 7:29 a.m. |
| PDg | Predicate description generation | batch_69f6fb17d5ec81909091e37e1ddbe577 |
completed | May 3, 2026, 7:36 a.m. |
Created at: May 1, 2026, 1:42 a.m.