Triple
T20356130
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tihar Jail |
E496651
|
entity |
| Predicate | numberOfJailsInComplex |
P139809
|
FINISHED |
| Object | 9 |
—
|
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: 9 | Statement: [Tihar Jail, numberOfJailsInComplex, 9]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfJailsInComplex Context triple: [Tihar Jail, numberOfJailsInComplex, 9]
-
A.
numberOfPrisonSentences
Indicates the count of distinct prison sentences that have been imposed on a given individual or entity.
-
B.
numberOfPrisonersApproximate
Indicates an approximate count of prisoners associated with an entity or situation, rather than an exact number.
-
C.
hasNumberOfArenasInComplex
Indicates the quantity of individual arenas contained within a larger arena complex.
-
D.
estimatedPrisonerCount
Indicates the estimated number of prisoners associated with a particular context, such as a location, time period, or event.
-
E.
hasJail
Indicates that one entity possesses, operates, or is associated with a jail or detention facility.
- 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_69e0b4a3f7f48190b37f354574028ca6 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e67853f10881908ecde94036804a8a |
completed | April 20, 2026, 7:02 p.m. |
| PD | Predicate disambiguation | batch_69e57636b4808190bc2855af48a3ccdc |
completed | April 20, 2026, 12:41 a.m. |
| PDg | Predicate description generation | batch_69e58d7481508190a87c8b88f9df9879 |
completed | April 20, 2026, 2:20 a.m. |
Created at: April 16, 2026, 11:25 a.m.