Triple
T14103400
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Call 9-1-1 |
E339438
|
entity |
| Predicate | usesProfanity |
P37187
|
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: [Call 9-1-1, usesProfanity, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesProfanity Context triple: [Call 9-1-1, usesProfanity, true]
-
A.
containsProfanity
chosen
Indicates that the referenced content includes one or more profane, vulgar, or offensive expressions.
-
B.
coCensorWith
Indicates that two or more entities participate together in the act of censoring the same content or subject.
-
C.
usesInclusiveLanguage
Indicates that the subject communicates in a way that avoids biased, exclusionary, or discriminatory language toward any group.
-
D.
usesWord
Indicates that one entity employs, contains, or makes use of a particular word in its expression, content, or communication.
-
E.
usedPhrase
Indicates that one entity employed or expressed a particular phrase in speech, writing, or another form of communication.
- 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_69d81c69b5c8819094aa1abf18302908 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de5fbd02888190bf07fd6d8769b61c |
completed | April 14, 2026, 3:39 p.m. |
| PD | Predicate disambiguation | batch_69de05b2f7e481908a9a7d40153234c0 |
completed | April 14, 2026, 9:15 a.m. |
Created at: April 9, 2026, 10:22 p.m.