Triple
T1323856
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | ARPANET Interface Message Processor platform |
E28280
|
entity |
| Predicate | alsoKnownAs |
P39
|
FINISHED |
| Object | IMP platform |
E4013
|
NE 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: IMP platform | Statement: [ARPANET Interface Message Processor platform, alsoKnownAs, IMP platform]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: IMP platform Context triple: [ARPANET Interface Message Processor platform, alsoKnownAs, IMP platform]
-
A.
IMP
chosen
IMP is an early packet-switching node used in the ARPANET, serving as a precursor to modern internet routers.
-
B.
Platform 1
Platform 1 is one of the passenger train platforms at Cambridge railway station in Cambridge, England.
-
C.
Platform 6
Platform 6 is one of the passenger train platforms at Cambridge railway station in Cambridge, England.
-
D.
GMT600 platform
The GMT600 platform is a General Motors architecture used for producing certain commercial vans and light-duty trucks.
-
E.
IPS
IPS is the premier all-India civil service responsible for leadership and command of police forces and law enforcement agencies across India.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69a498540a2481909e807a762280d3ba |
completed | March 1, 2026, 7:49 p.m. |
| NER | Named-entity recognition | batch_69a4c19caa148190a1f5be734b7d9005 |
completed | March 1, 2026, 10:45 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69acbf2e13dc8190902879be5fa69adb |
completed | March 8, 2026, 12:13 a.m. |
Created at: March 1, 2026, 7:55 p.m.