Triple
T1056973
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Euclidean space |
E22816
|
entity |
| Predicate | isLocallyCompact |
P22988
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Euclidean space, isLocallyCompact, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isLocallyCompact Context triple: [Euclidean space, isLocallyCompact, true]
-
A.
localityCondition
Indicates a spatial or contextual constraint specifying where or under what local conditions a relationship, event, or property holds.
-
B.
representedLocallyBy
Indicates that an entity is expressed, implemented, or instantiated in a specific local form or representation by another entity.
-
C.
hasTypeLocality
Indicates the specific geographic location where an entity (typically a species or specimen) was originally found and formally described.
-
D.
isLocalQuantity
Indicates that a quantity is specific to a particular context, location, or subsystem rather than being globally applicable.
-
E.
isLocalLandmark
Indicates that something is recognized as a notable or significant landmark within a specific local area or community.
- 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_69a493dada0481909c43649f9843ea91 |
completed | March 1, 2026, 7:30 p.m. |
| NER | Named-entity recognition | batch_69a4b8da80dc8190b79beaf509910725 |
completed | March 1, 2026, 10:08 p.m. |
| PD | Predicate disambiguation | batch_69a4b731e25c8190b5ea8466648c2c9a |
completed | March 1, 2026, 10:01 p.m. |
| PDg | Predicate description generation | batch_69a4b7da38888190a118ef20ce4ae9aa |
completed | March 1, 2026, 10:04 p.m. |
Created at: March 1, 2026, 7:42 p.m.