Triple
T11857243
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Thinking Machines Corporation WAIS project |
E282069
|
entity |
| Predicate | retrievalModel |
P535
|
FINISHED |
| Object | full-text retrieval |
—
|
LITERAL 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: full-text retrieval | Statement: [Thinking Machines Corporation WAIS project, retrievalModel, full-text retrieval]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: retrievalModel Context triple: [Thinking Machines Corporation WAIS project, retrievalModel, full-text retrieval]
-
A.
model
Indicates that one entity serves as a representation, example, or simulation of another entity or concept.
-
B.
dataModel
chosen
Indicates a relationship where an entity defines, uses, or is structured according to a specific data model or schema.
-
C.
notableModel
Indicates that an entity is a particularly important, influential, or exemplary instance or version within a broader category or system.
-
D.
emblematicModel
Indicates that one entity serves as a representative or symbolic example of another entity, capturing its defining characteristics or ideals.
-
E.
coverModelSelection
Indicates selecting or designating a particular model to appear on the cover of a publication or media item.
- F. None of above.
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_69d6ab287ba48190a5178779fd19b9b7 |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d8a699089c8190b7a298baf13dcded |
completed | April 10, 2026, 7:28 a.m. |
| PD | Predicate disambiguation | batch_69d8a2573dbc8190ab432e8e28fde6cc |
completed | April 10, 2026, 7:10 a.m. |
Created at: April 8, 2026, 9:43 p.m.