Triple
T52586
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | ARPANET |
E1032
|
entity |
| Predicate | usesTechnology |
P1485
|
FINISHED |
| Object | IMP |
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 | Statement: [ARPANET, usesTechnology, IMP]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: IMP Context triple: [ARPANET, usesTechnology, IMP]
-
A.
IMP
chosen
IMP is an early packet-switching node used in the ARPANET, serving as a precursor to modern internet routers.
-
B.
IN
IN is the two-letter ISO 3166-1 alpha-2 country code representing India in international standards and systems.
-
C.
OM
OM is the post-nominal abbreviation used by members of the Order of Merit, a prestigious British honor recognizing distinguished service in the armed forces, science, art, literature, or the promotion of culture.
-
D.
PT
PT is the two-letter ISO 3166-1 alpha-2 country code that uniquely identifies Portugal in international standards and systems.
-
E.
HUP
HUP is a major academic medical center in Philadelphia that serves as the flagship teaching hospital of the University of Pennsylvania's health system.
- 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_69a2480baefc81909951b14058479aa2 |
completed | Feb. 28, 2026, 1:42 a.m. |
| NER | Named-entity recognition | batch_69a24ec4d84c81908d85a1e941dbcd19 |
completed | Feb. 28, 2026, 2:11 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a255381a7c8190a48bee7032c622bb |
completed | Feb. 28, 2026, 2:38 a.m. |
Created at: Feb. 28, 2026, 1:47 a.m.