Triple
T4661774
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lemaître–Tolman metric |
E102548
|
entity |
| Predicate | doesNotAssume |
P3442
|
FINISHED |
| Object | spatial homogeneity |
—
|
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: spatial homogeneity | Statement: [Lemaître–Tolman metric, doesNotAssume, spatial homogeneity]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: doesNotAssume Context triple: [Lemaître–Tolman metric, doesNotAssume, spatial homogeneity]
-
A.
doesNot
Indicates that a specified entity lacks, refrains from, or fails to perform a particular action or exhibit a particular property in relation to another entity or context.
-
B.
doesNotUse
Indicates that one entity intentionally refrains from employing, utilizing, or relying on another entity, method, or resource.
-
C.
doesNotImply
chosen
Indicates that the truth of one statement or condition does not guarantee or lead to the truth of another statement or condition.
-
D.
doesNotConsider
Indicates that one entity fails or chooses not to take another entity or factor into account when forming judgments, decisions, or actions.
-
E.
doesNotTry
Indicates that an entity makes no attempt to perform a particular action or engage in a specified activity.
- 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_69bd43d823288190952279faa0d1d066 |
completed | March 20, 2026, 12:55 p.m. |
| NER | Named-entity recognition | batch_69bd632b7fb88190821f213620719d6b |
completed | March 20, 2026, 3:09 p.m. |
| PD | Predicate disambiguation | batch_69bd62126b0c81909ba3f21b21e30d54 |
completed | March 20, 2026, 3:04 p.m. |
Created at: March 20, 2026, 1:15 p.m.