Triple
T1197864
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Indian Police Service |
E25708
|
entity |
| Predicate | trainingDurationApprox |
P17474
|
FINISHED |
| Object | about two years including field training |
—
|
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: about two years including field training | Statement: [Indian Police Service, trainingDurationApprox, about two years including field training]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: trainingDurationApprox Context triple: [Indian Police Service, trainingDurationApprox, about two years including field training]
-
A.
timeToComplete
chosen
Indicates the duration required for an entity or process to be fully completed.
-
B.
typicalDurationDays
Indicates the usual or expected number of days that an associated event, process, or state typically lasts.
-
C.
possibleDuration
Indicates the range or specific length of time that an action, event, or state can last or is allowed to last.
-
D.
missionDurationType
Indicates the classification of a mission’s length or time span (e.g., short-term, long-term, extended).
-
E.
transmissionDuration
Indicates the length of time over which a transmission or transfer of data, signal, or content occurs.
- 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_69a49429f5ec8190a6a205eb0ae81e5e |
completed | March 1, 2026, 7:31 p.m. |
| NER | Named-entity recognition | batch_69a4bd9c013c8190822d44d465d60fdb |
completed | March 1, 2026, 10:28 p.m. |
| PD | Predicate disambiguation | batch_69a4bb5d40a08190b7682d8ef8075421 |
completed | March 1, 2026, 10:19 p.m. |
Created at: March 1, 2026, 7:46 p.m.