Triple
T957632
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | WirelessHART |
E20658
|
entity |
| Predicate | basedOn |
P98
|
FINISHED |
| Object | HART |
E20658
|
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: HART | Statement: [WirelessHART, basedOn, HART]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: HART Context triple: [WirelessHART, basedOn, HART]
-
A.
HART
HART is the public bus transportation system serving the Huntington area, providing local transit services to residents and visitors.
-
B.
WirelessHART
chosen
WirelessHART is an industrial wireless communication standard designed for reliable, secure, and interoperable field device networking in process automation environments.
-
C.
Honeywell 316
The Honeywell 316 is a 16-bit minicomputer introduced in the late 1960s, used widely for real-time control, industrial, and embedded applications.
-
D.
Hart
Hart is a surname most famously associated with Moss Hart, the acclaimed American playwright and theater director known for works like "You Can't Take It with You" and "Once in a Lifetime."
-
E.
Honeywell
Honeywell is a multinational conglomerate best known for its aerospace systems, building technologies, performance materials, and industrial automation products.
- 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_69a493b21f2881908132dcf45dcd2f36 |
completed | March 1, 2026, 7:29 p.m. |
| NER | Named-entity recognition | batch_69a4b3fac2bc8190a66feb70c68899b2 |
completed | March 1, 2026, 9:47 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a933b259d08190b03989e2b1575085 |
completed | March 5, 2026, 7:41 a.m. |
Created at: March 1, 2026, 7:40 p.m.