Triple
T12515027
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | objcopy |
E299171
|
entity |
| Predicate | hasManualPage |
P76519
|
FINISHED |
| Object | objcopy(1) |
—
|
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: objcopy(1) | Statement: [objcopy, hasManualPage, objcopy(1)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasManualPage Context triple: [objcopy, hasManualPage, objcopy(1)]
-
A.
hasManual
chosen
Indicates that an entity is associated with a manual that provides instructions or documentation for it.
-
B.
hasPage
Indicates that one entity includes, is associated with, or is documented by a specific page (such as a web page or document page).
-
C.
hasPageCountApprox
Indicates that an entity is associated with an approximate or estimated number of pages, rather than an exact page count.
-
D.
hasProjectInformationPage
Indicates that an entity is associated with a specific web page or resource that provides detailed information about a project.
-
E.
hasNonManualMarkers
Indicates that a sign or gesture is accompanied by specific non-manual features (such as facial expressions, head or body movements) that contribute to its grammatical or semantic meaning.
- 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_69d6ada5cdd48190860d9ce30aff69be |
completed | April 8, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69d954b867dc8190af8a70f797e4d133 |
completed | April 10, 2026, 7:51 p.m. |
| PD | Predicate disambiguation | batch_69d954096af88190b6be81b008c82139 |
completed | April 10, 2026, 7:48 p.m. |
Created at: April 8, 2026, 9:57 p.m.