Triple
T29514438
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Graham–Pollak theorem |
E748752
|
entity |
| Predicate | tightness |
P166987
|
FINISHED |
| Object | The bound n−1 is best possible. |
—
|
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: The bound n−1 is best possible. | Statement: [Graham–Pollak theorem, tightness, The bound n−1 is best possible.]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: tightness Context triple: [Graham–Pollak theorem, tightness, The bound n−1 is best possible.]
-
A.
tightens
Indicates that one entity makes another entity more secure, compact, or taut by applying constricting force or reducing looseness.
-
B.
tightFor
Indicates that one entity fits another with little or no extra space, suggesting a close or constraining fit.
-
C.
tension
Indicates a state of strain, stress, or conflict existing between entities, often involving opposing forces, interests, or emotions.
-
D.
isTight
Indicates that one entity fits closely or securely around, against, or within another without looseness or extra space.
-
E.
hasTension
Indicates the presence of strain, stress, or conflict between entities in their relationship or interaction.
- F. None of above. chosen
Provenance (4 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_69f0bd461c208190bec20bbf24e02cc5 |
completed | April 28, 2026, 1:59 p.m. |
| NER | Named-entity recognition | batch_69f66c62719c8190852726ede476e159 |
completed | May 2, 2026, 9:28 p.m. |
| PD | Predicate disambiguation | batch_69f6633ac8a88190ab0cda62bbfcf9b0 |
completed | May 2, 2026, 8:48 p.m. |
| PDg | Predicate description generation | batch_69f6642e676c8190af0e6b1416eed6d2 |
completed | May 2, 2026, 8:53 p.m. |
Created at: April 28, 2026, 4:35 p.m.