Triple
T33687740
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tangere |
E863086
|
entity |
| Predicate | famousUsageTranslation |
P58306
|
FINISHED |
| Object | Do not touch me |
—
|
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: Do not touch me | Statement: [Tangere, famousUsageTranslation, Do not touch me]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: famousUsageTranslation Context triple: [Tangere, famousUsageTranslation, Do not touch me]
-
A.
usedToTranslate
Indicates that one entity served as the tool, method, or medium for translating another entity from one language or representation to another.
-
B.
isFamouslyUsedBy
Indicates that something is widely and notably used by a particular person, group, or entity, in a way that is broadly recognized or associated with them.
-
C.
isFamouslyUsedIn
chosen
Indicates that something is widely recognized or well-known for being used in a particular context, work, or situation.
-
D.
translationUsedAs
Indicates that one translation of a text, phrase, or term is employed or treated as another specific translation in a given context.
-
E.
fameFor
Indicates that one entity is widely known or recognized specifically because of, or in connection with, another entity.
- 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_69f3498662b48190904442c39df84fb7 |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69f7051ad6e4819095e82bbd64761803 |
completed | May 3, 2026, 8:19 a.m. |
| PD | Predicate disambiguation | batch_69f700fe24e08190998e2c96fbaaad38 |
completed | May 3, 2026, 8:02 a.m. |
Created at: May 1, 2026, 1:43 a.m.