Triple
T31742995
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Muhammad Ahsan Dar |
E810188
|
entity |
| Predicate | occupationBeforeMilitancy |
P109825
|
FINISHED |
| Object | school teacher |
—
|
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: school teacher | Statement: [Muhammad Ahsan Dar, occupationBeforeMilitancy, school teacher]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: occupationBeforeMilitancy Context triple: [Muhammad Ahsan Dar, occupationBeforeMilitancy, school teacher]
-
A.
professionBeforePolitics
chosen
Indicates that a person’s occupation or career occurred prior to their involvement in politics.
-
B.
earlierOccupation
Indicates that one occupation held by an entity occurred before another occupation in that entity’s work history.
-
C.
formerEconomicActivity
Indicates that an entity previously engaged in a specified economic activity but no longer does so.
-
D.
hasPastOccupation
Indicates that an entity previously held a particular job, role, or occupation in the past.
-
E.
occupationType
Indicates the specific kind or category of work, profession, or role that an entity performs or holds.
- 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_69f348e233cc819083b6695f70cd75d8 |
completed | April 30, 2026, 12:19 p.m. |
| NER | Named-entity recognition | batch_69f6c1bb5f248190834161b5a6ba1ece |
completed | May 3, 2026, 3:32 a.m. |
| PD | Predicate disambiguation | batch_69f6bd25bed08190befcabd3a41ffadf |
completed | May 3, 2026, 3:12 a.m. |
Created at: April 30, 2026, 11:25 p.m.