Triple
T37173339
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | King’s Handbook of New York City |
E920972
|
entity |
| Predicate | illustration |
P187502
|
FINISHED |
| Object | richly illustrated |
—
|
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: richly illustrated | Statement: [King’s Handbook of New York City, illustration, richly illustrated]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: illustration Context triple: [King’s Handbook of New York City, illustration, richly illustrated]
-
A.
artwork
Indicates that one entity is an artwork created, presented, or associated with another entity (such as an artist, collection, or institution).
-
B.
genreIllustrated
Indicates that one entity is a genre that is exemplified or visually represented by the other entity.
-
C.
illustratedAs
Indicates that one entity is visually depicted or represented in the form or style of another entity.
-
D.
oftenIllustratedBy
Indicates that something is frequently depicted, represented, or exemplified through a particular image, example, or illustration.
-
E.
architecturalIllustrationsBy
Indicates a relationship where one entity has produced or created architectural illustrations for another entity.
- F. None of above. chosen
Provenance (4 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_69f76ea16f288190b445aa1604d996f4 |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_69fb55de3b9c8190a7656aeab3c3ffbc |
completed | May 6, 2026, 2:53 p.m. |
| PD | Predicate disambiguation | batch_69fb35bc92e08190bff447624e2df791 |
completed | May 6, 2026, 12:36 p.m. |
| PDg | Predicate description generation | batch_69fb55dc36d08190a0634fa680e13114 |
completed | May 6, 2026, 2:53 p.m. |
Created at: May 3, 2026, 4:15 p.m.