Triple
T1107056
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chief Justice of India |
E25508
|
entity |
| Predicate | officeHoldersNumbered |
P23221
|
FINISHED |
| Object | sequentially from 1 onward |
—
|
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: sequentially from 1 onward | Statement: [Chief Justice of India, officeHoldersNumbered, sequentially from 1 onward]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: officeHoldersNumbered Context triple: [Chief Justice of India, officeHoldersNumbered, sequentially from 1 onward]
-
A.
officeHoldersNumber
Indicates the number of individuals who hold a particular office or position.
-
B.
officeHolders
Indicates a relationship where one or more entities hold, or have held, an official position or role within a specified organization, institution, or jurisdiction.
-
C.
officeHoldersCollectively
Indicates that a group of individuals jointly hold, or have held, a particular office or set of offices as a collective body.
-
D.
firstOfficeHoldersCount
Indicates the number of individuals who initially held a particular office or position.
-
E.
officeHolderOf
Indicates that a person holds or has held an official position or role within a specified organization, institution, or office.
- 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_69a49428d4448190b3b36991ceae87ce |
completed | March 1, 2026, 7:31 p.m. |
| NER | Named-entity recognition | batch_69a4b9e47e4881908928900df72781f0 |
completed | March 1, 2026, 10:12 p.m. |
| PD | Predicate disambiguation | batch_69a4b74877748190b78cd8847ee4fa7a |
completed | March 1, 2026, 10:01 p.m. |
| PDg | Predicate description generation | batch_69a4b7da38888190a118ef20ce4ae9aa |
completed | March 1, 2026, 10:04 p.m. |
Created at: March 1, 2026, 7:43 p.m.