Triple
T37457977
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Life Tap |
E930845
|
entity |
| Predicate | localizedIn |
P190537
|
FINISHED |
| Object | Multiple languages |
—
|
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: Multiple languages | Statement: [Life Tap, localizedIn, Multiple languages]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: localizedIn Context triple: [Life Tap, localizedIn, Multiple languages]
-
A.
localization
Indicates the spatial or contextual placement of one entity relative to another or within a specific environment.
-
B.
localizationBy
Indicates a relationship where one entity determines, specifies, or constrains the spatial or contextual location of another entity.
-
C.
locale
Indicates that one entity is the place, setting, or geographic area in which another entity exists, occurs, or is situated.
-
D.
localizationInHuman
Indicates the anatomical or cellular location of something specifically within the human body.
-
E.
languageUsedInLocality
Indicates that a particular language is used or spoken within a specific locality or geographic area.
- 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_69f76ec1a1148190b0a961f188d621b0 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69fcc7779d248190afdb348a95375443 |
completed | May 7, 2026, 5:10 p.m. |
| PD | Predicate disambiguation | batch_69fcc58566a0819082d5ea36e03bf0c6 |
completed | May 7, 2026, 5:01 p.m. |
| PDg | Predicate description generation | batch_69fcc73264e08190b0b5917f32226fae |
completed | May 7, 2026, 5:09 p.m. |
Created at: May 3, 2026, 4:17 p.m.