Triple
T14783
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | David Packard |
E295
|
entity |
| Predicate | employer |
P7
|
FINISHED |
| Object | Hewlett-Packard |
E7429
|
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: Hewlett-Packard | Statement: [David Packard, employer, Hewlett-Packard]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hewlett-Packard Context triple: [David Packard, employer, Hewlett-Packard]
-
A.
Hewlett-Packard
chosen
Hewlett-Packard is a pioneering American technology company known for its innovations in computing, printers, and enterprise IT solutions.
-
B.
IBM
IBM is a multinational technology and consulting company known for its pioneering work in computer hardware, software, and enterprise services.
-
C.
Intel Corporation
Intel Corporation is a leading American semiconductor company best known for designing and manufacturing microprocessors that power the majority of the world’s personal computers and servers.
-
D.
Cisco Systems
Cisco Systems is a multinational technology conglomerate best known for designing and selling networking hardware, software, and telecommunications equipment used worldwide.
-
E.
Apple Inc.
Apple Inc. is a multinational technology company best known for designing and selling consumer electronics like the iPhone, Mac, and iPad, along with software and digital services.
- 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_69a23d7ad88c8190bffe8ab091d86642 |
completed | Feb. 28, 2026, 12:57 a.m. |
| NER | Named-entity recognition | batch_69a2400257208190b3cd87ad2a06c18f |
completed | Feb. 28, 2026, 1:08 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a26237c7208190ac4a1c373ff37b06 |
completed | Feb. 28, 2026, 3:34 a.m. |
Created at: Feb. 28, 2026, 1:02 a.m.