Triple
T31385122
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | New Square, New York |
E800573
|
entity |
| Predicate | dressCodeCharacteristic |
P110046
|
FINISHED |
| Object | traditional Hasidic dress |
—
|
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: traditional Hasidic dress | Statement: [New Square, New York, dressCodeCharacteristic, traditional Hasidic dress]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: dressCodeCharacteristic Context triple: [New Square, New York, dressCodeCharacteristic, traditional Hasidic dress]
-
A.
coatCharacteristic
Indicates that one entity has a particular property, feature, or quality that characterizes its outer covering or surface.
-
B.
fashionCharacteristic
Indicates a relationship where one entity possesses or exhibits a particular style, trend, or fashion-related attribute in relation to another.
-
C.
dressFeature
Indicates that a dress possesses or is characterized by a particular feature, attribute, or design element.
-
D.
clothingFeature
chosen
Indicates that one entity has a specific clothing-related attribute, detail, or characteristic associated with it.
-
E.
garmentType
Indicates the specific kind or category of garment associated with an 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_69f224e9d7048190b0cc20f9071bd3e4 |
completed | April 29, 2026, 3:34 p.m. |
| NER | Named-entity recognition | batch_69f6a0ea04888190ac3a813b603bcb5c |
completed | May 3, 2026, 1:12 a.m. |
| PD | Predicate disambiguation | batch_69f69fe463248190aa78128abeab1183 |
completed | May 3, 2026, 1:07 a.m. |
Created at: April 29, 2026, 9:19 p.m.