Triple
T22064623
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | CSE |
E545235
|
entity |
| Predicate | recruitsFor |
P28396
|
FINISHED |
| Object | IPS |
—
|
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: IPS | Statement: [CSE, recruitsFor, IPS]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: IPS Context triple: [CSE, recruitsFor, IPS]
-
A.
IPS
IPS is the acronym for the Israel Prison Service, the government agency responsible for managing prisons and detention facilities in Israel.
-
B.
IPS
chosen
IPS is the premier all-India civil service responsible for leadership and command of police forces and law enforcement agencies across India.
-
C.
IPS
IPS is a professional society within the IEEE focused on the science and technology of light, including photonics and optoelectronics.
-
D.
IPS
IPS is the National Rail station code used to identify Ipswich railway station in Suffolk, England.
-
E.
IPP
IPP (Internet Printing Protocol) is a modern network printing protocol that supports advanced features like secure, authenticated printing and detailed job management over IP-based networks.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e11e344dfc81909b1d88a7221329c7 |
completed | April 16, 2026, 5:36 p.m. |
| NER | Named-entity recognition | batch_69f12882ab3c819095b61e0a341edfdf |
completed | April 28, 2026, 9:37 p.m. |
Created at: April 16, 2026, 8:27 p.m.