Triple
T30819787
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | National Monuments in New York City |
E784883
|
entity |
| Predicate | comprisesSitesIn |
P5003
|
FINISHED |
| Object | Manhattan |
—
|
NE NERFINISHED |
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: Manhattan | Statement: [National Monuments in New York City, comprisesSitesIn, Manhattan]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: comprisesSitesIn Context triple: [National Monuments in New York City, comprisesSitesIn, Manhattan]
-
A.
containsSite
chosen
Indicates that one entity spatially or structurally includes another entity as a site or location within its bounds.
-
B.
isTypeSiteOf
Indicates that a site serves as the specific location or setting where a particular type, category, or classification is realized or occurs.
-
C.
isSiteOf
Indicates that a location or place serves as the setting or host for a particular event, activity, or feature.
-
D.
isSatelliteSiteOf
Indicates that one site functions as a subsidiary, dependent, or secondary location associated with another primary or main site.
-
E.
numberOfSites
Indicates the total count of distinct sites associated with or involved in the given entity or context.
- 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_69f224b4eda48190bd212ce4f3901e56 |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69f6906b8f048190b3051f9ece75bd3a |
completed | May 3, 2026, 12:01 a.m. |
| PD | Predicate disambiguation | batch_69f68b7d2794819092fef8a63f4f3de8 |
completed | May 2, 2026, 11:40 p.m. |
Created at: April 29, 2026, 8:44 p.m.