Triple
T31656297
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | New New York City |
E807865
|
entity |
| Predicate | containsBelowInFiction |
P200546
|
FINISHED |
| Object | Old New York |
—
|
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: Old New York | Statement: [New New York City, containsBelowInFiction, Old New York]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: containsBelowInFiction Context triple: [New New York City, containsBelowInFiction, Old New York]
-
A.
hasRelativeInFiction
Indicates that one entity has a relative or family member who appears as a character within a fictional work associated with the other entity.
-
B.
hasChildInFiction
Indicates that a fictional work or character includes another character as their child within the fictional narrative.
-
C.
showWithinFiction
Indicates that one entity is depicted, referenced, or occurs as part of the fictional world or narrative context of another entity.
-
D.
eraWithinFiction
Indicates that a time period or era exists inside the narrative world or timeline of a fictional work.
-
E.
hasPlaceInFiction
Indicates that a fictional work or element is associated with, set in, or takes place within a particular fictional location or setting.
- 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_69f348daf95c81908b4c985b7ddcd0b3 |
completed | April 30, 2026, 12:19 p.m. |
| NER | Named-entity recognition | batch_69ff956dc6548190979171d4b4068d47 |
completed | May 9, 2026, 8:13 p.m. |
| PD | Predicate disambiguation | batch_69ff93dc39c481908a97a12c3ef7dfe7 |
completed | May 9, 2026, 8:06 p.m. |
| PDg | Predicate description generation | batch_69ff956cd640819081efc31f313690b0 |
completed | May 9, 2026, 8:13 p.m. |
Created at: April 30, 2026, 10:55 p.m.