Triple
T28732689
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | QM2 |
E730702
|
entity |
| Predicate | primaryDestinationBorough |
P202332
|
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: [QM2, primaryDestinationBorough, Manhattan]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: primaryDestinationBorough Context triple: [QM2, primaryDestinationBorough, Manhattan]
-
A.
primaryBorough
Indicates that one borough is the main or most significant borough associated with a given entity.
-
B.
primaryBoroughFocus
Indicates that something has its main or most significant emphasis, activity, or attention centered on a particular borough.
-
C.
originBorough
Indicates that one entity originates from, or is originally associated with, a specific borough.
-
D.
positionInBorough
Indicates that one entity is located within or belongs to the geographic area of a specific borough.
-
E.
secondaryBorough
Indicates that an entity is located in, associated with, or assigned to a secondary (non-primary) borough within a larger municipal or administrative structure.
- 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_69f043eae0908190b28ce314686247d7 |
completed | April 28, 2026, 5:21 a.m. |
| NER | Named-entity recognition | batch_6a007338002081908cb6340d65ff86d5 |
completed | May 10, 2026, 11:59 a.m. |
| PD | Predicate disambiguation | batch_6a0072a137ac8190a7debeb28e738e03 |
completed | May 10, 2026, 11:57 a.m. |
| PDg | Predicate description generation | batch_6a00733756848190b94524b42d6edf0a |
completed | May 10, 2026, 11:59 a.m. |
Created at: April 28, 2026, 5:59 a.m.