Triple
T35196377
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | We Wear the Mask |
E1016271
|
entity |
| Predicate | pronounUsage |
P29199
|
FINISHED |
| Object | we |
—
|
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: we | Statement: [We Wear the Mask, pronounUsage, we]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: pronounUsage Context triple: [We Wear the Mask, pronounUsage, we]
-
A.
hasSubjectPronouns
Indicates that an entity is associated with one or more pronouns that function as its grammatical subject in sentences.
-
B.
linguisticUsage
chosen
Indicates how a linguistic form, expression, or construction is used in language, such as its typical context, function, or register.
-
C.
hasDistinctPronounsFrom
Indicates that two entities use different sets of pronouns from each other.
-
D.
usesAnaphora
Indicates that one entity refers back to another previously mentioned entity using anaphoric expression (e.g., pronouns or repeated phrases).
-
E.
hasPronounForIt
Indicates that one entity serves as the pronoun form referring to 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_69f76dde814c8190a71f60d514a424a4 |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69f78e3148d8819098eb57e1671bf9c0 |
completed | May 3, 2026, 6:04 p.m. |
| PD | Predicate disambiguation | batch_69f78b9106008190930b3b3675b737d6 |
completed | May 3, 2026, 5:53 p.m. |
Created at: May 3, 2026, 4:02 p.m.