Triple
T26992654
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Computers and Intractability: A Guide to the Theory of NP-Completeness |
E679895
|
entity |
| Predicate | canonicalAbbreviation |
P99168
|
FINISHED |
| Object | G&J |
—
|
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: G&J | Statement: [Computers and Intractability: A Guide to the Theory of NP-Completeness, canonicalAbbreviation, G&J]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: canonicalAbbreviation Context triple: [Computers and Intractability: A Guide to the Theory of NP-Completeness, canonicalAbbreviation, G&J]
-
A.
alternativeAbbreviation
Indicates that one term serves as an alternative shortened form or acronym for another term.
-
B.
abbreviationOrShortForm
chosen
Indicates that one term is an abbreviation or shortened form of another term.
-
C.
isCommonAbbreviation
Indicates that one term is a widely used shortened or abbreviated form of another term.
-
D.
typeOfAbbreviation
Indicates that one term is an abbreviation of a specific type or category (e.g., acronym, initialism) of another expression.
-
E.
abbreviationUsedFor
Indicates that a particular shortened form or acronym is used to represent or stand in for a longer term, name, or expression.
- 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_69eeeb5138ac8190b3c273ddc659a54f |
completed | April 27, 2026, 4:51 a.m. |
| NER | Named-entity recognition | batch_69f62d53ad58819080c5227c7a729d15 |
completed | May 2, 2026, 4:58 p.m. |
| PD | Predicate disambiguation | batch_69f62c15952881908a5ea0c25904afec |
completed | May 2, 2026, 4:53 p.m. |
Created at: April 27, 2026, 6:53 a.m.