Triple
T4088406
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | New Havener |
E87645
|
entity |
| Predicate | mayBeSubjectOf |
P52935
|
FINISHED |
| Object | New Haven local laws |
—
|
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: New Haven local laws | Statement: [New Havener, mayBeSubjectOf, New Haven local laws]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: mayBeSubjectOf Context triple: [New Havener, mayBeSubjectOf, New Haven local laws]
-
A.
hasBeenSubjectOf
Indicates that an entity has previously been the focus or target of a particular action, process, or investigation.
-
B.
subjectCanBe
Indicates that the subject has the potential or capability to assume, become, or be classified as the specified object or state.
-
C.
subjectOfCatalog
Indicates that something is the primary focus or entry described within a catalog or cataloging record.
-
D.
isAssociatedWith
Indicates that there exists a connection, relationship, or involvement between two entities without specifying its exact nature.
-
E.
depictedSubject
Indicates that one entity visually represents or portrays another entity as its subject in an image or depiction.
- 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_69aed94425148190be337845d56fac22 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aefca9e9088190a97cb2ccb5d622f0 |
completed | March 9, 2026, 5 p.m. |
| PD | Predicate disambiguation | batch_69aef909c9c88190b09d48dad325a83c |
completed | March 9, 2026, 4:44 p.m. |
| PDg | Predicate description generation | batch_69aef9b34dec81909bbc3def9decc71a |
completed | March 9, 2026, 4:47 p.m. |
Created at: March 9, 2026, 3:39 p.m.