Triple
T179423
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | implicit function theorem |
E3650
|
entity |
| Predicate | typicalAssumption |
P7027
|
FINISHED |
| Object | F is Ck with k≥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: F is Ck with k≥1 | Statement: [implicit function theorem, typicalAssumption, F is Ck with k≥1]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalAssumption Context triple: [implicit function theorem, typicalAssumption, F is Ck with k≥1]
-
A.
assumes
Indicates that one entity takes on, accepts, or presumes a role, responsibility, state, or fact regarding another entity or situation.
-
B.
typicalBackground
Indicates that an entity has a usual or commonly expected background, context, or setting associated with it.
-
C.
typicalSpeaker
Indicates that the subject is a prototypical or characteristic speaker or source of utterances in the context of the object.
-
D.
typicalSchedule
Indicates the usual or standard timing and sequence of activities or events associated with an entity.
-
E.
usuallyAccompaniedBy
Indicates that one entity is commonly or habitually found together with, or occurs in the presence of, another entity.
- 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_69a25374990081909766d30c79a18e0e |
completed | Feb. 28, 2026, 2:31 a.m. |
| NER | Named-entity recognition | batch_69a25900709c8190a65e778936be5dd5 |
completed | Feb. 28, 2026, 2:54 a.m. |
| PD | Predicate disambiguation | batch_69a2566b53d481909c0ed40dd3719e8c |
completed | Feb. 28, 2026, 2:43 a.m. |
| PDg | Predicate description generation | batch_69a2582b7f648190b0ef676b8bdc1c65 |
completed | Feb. 28, 2026, 2:51 a.m. |
Created at: Feb. 28, 2026, 2:39 a.m.