Triple
T19177337
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | HAL 9000 |
E469472
|
entity |
| Predicate | inUniverseManufacturer |
P83931
|
FINISHED |
| Object | HAL Laboratories |
—
|
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: HAL Laboratories | Statement: [HAL 9000, inUniverseManufacturer, HAL Laboratories]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: HAL Laboratories Context triple: [HAL 9000, inUniverseManufacturer, HAL Laboratories]
-
A.
Tartan Laboratories
Tartan Laboratories was a computer science and software company known for its work on programming language tools and compilers, particularly in collaboration with prominent language designers like Guy L. Steele Jr.
-
B.
HAL Laboratory
chosen
HAL Laboratory is a Japanese video game developer best known for creating the Kirby series and contributing to the Super Smash Bros. franchise.
-
C.
Xtreme Labs
Xtreme Labs was a mobile app development company known for building high-profile applications and later becoming part of Pivotal Labs.
-
D.
Hatch Labs
Hatch Labs is a mobile technology incubator and startup studio best known for creating the popular dating app Tinder.
-
E.
Deluxe Laboratories
Deluxe Laboratories is a prominent film processing and post-production company known for its work with color motion picture technologies.
- 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_69d8dd09d5a081909ae43c286651ae5a |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5f618f18c8190b98995fda4b6fea0 |
completed | April 20, 2026, 9:47 a.m. |
Created at: April 10, 2026, 12:07 p.m.