Triple
T5115216
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | five boroughs of New York City |
E115314
|
entity |
| Predicate | differIn |
P61682
|
FINISHED |
| Object | population |
—
|
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: population | Statement: [five boroughs of New York City, differIn, population]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: differIn Context triple: [five boroughs of New York City, differIn, population]
-
A.
isDistinctFrom
Indicates that two entities are not identical and can be clearly distinguished from one another.
-
B.
mayDifferFrom
Indicates that one entity is allowed or expected to be different from another entity, without requiring them to be identical.
-
C.
isInterpretedDifferentlyIn
Indicates that the same item, event, or expression is understood or construed in a different way within a specified context, group, or setting.
-
D.
hasLexicalDifferencesWith
Indicates that two linguistic items differ from each other in their word choice or lexical form.
-
E.
differenceFromStates
Indicates that one state or condition is distinct from, or deviates in some way from, another state or condition.
- 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_69bd4441d1648190a54a533895041987 |
completed | March 20, 2026, 12:57 p.m. |
| NER | Named-entity recognition | batch_69bd75ce6044819094166aebf0688665 |
completed | March 20, 2026, 4:29 p.m. |
| PD | Predicate disambiguation | batch_69bd715fe3a8819087d3065adddba515 |
completed | March 20, 2026, 4:10 p.m. |
| PDg | Predicate description generation | batch_69bd72e1b7cc8190b2e621fdf8f22e38 |
completed | March 20, 2026, 4:16 p.m. |
Created at: March 20, 2026, 1:41 p.m.