Triple
T13439281
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pat (Saturday Night Live) |
E320311
|
entity |
| Predicate | nameCharacteristic |
P99469
|
FINISHED |
| Object | intentionally gender-neutral given name |
—
|
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: intentionally gender-neutral given name | Statement: [Pat (Saturday Night Live), nameCharacteristic, intentionally gender-neutral given name]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: nameCharacteristic Context triple: [Pat (Saturday Night Live), nameCharacteristic, intentionally gender-neutral given name]
-
A.
themeCharacteristic
Indicates that a characteristic, quality, or property is attributed to or associated with a particular theme.
-
B.
featuresCharacterWith
Indicates that one entity (such as a work or product) includes or presents a particular character as part of its content.
-
C.
characterName
Indicates that an entity has a specific name used to identify its character.
-
D.
subjectHasCharacteristic
chosen
Indicates that a subject possesses, exhibits, or is defined by a particular characteristic or attribute.
-
E.
associatedCharacterTrait
Indicates a relationship where a character is linked to, or described by, a particular trait or quality.
- 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_69d80761e6cc8190a90c844589998ecc |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dbaee5ec488190bd0c1e990dbd2bc2 |
completed | April 12, 2026, 2:40 p.m. |
| PD | Predicate disambiguation | batch_69d9a03926188190ab3948d1f5d3941f |
completed | April 11, 2026, 1:13 a.m. |
Created at: April 9, 2026, 9:40 p.m.