Triple
T13989941
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dayton, New Jersey |
E336541
|
entity |
| Predicate | hasSecondaryResidentialCharacter |
P90082
|
FINISHED |
| Object | townhouses |
—
|
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: townhouses | Statement: [Dayton, New Jersey, hasSecondaryResidentialCharacter, townhouses]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSecondaryResidentialCharacter Context triple: [Dayton, New Jersey, hasSecondaryResidentialCharacter, townhouses]
-
A.
isResidential
Indicates that something is used or designated primarily for people to live in, rather than for commercial, industrial, or other non-living purposes.
-
B.
isResidentialUnitOf
Indicates that a specific residential unit (e.g., apartment, house) belongs to or is part of a larger property, building, or complex.
-
C.
hasSecondary
chosen
Indicates that an entity is associated with an additional or subordinate counterpart beyond its primary one.
-
D.
hasResidentialArea
Indicates that an entity includes, contains, or is associated with an area designated for people to live or reside.
-
E.
ownedResidence
Indicates that one entity has ownership of a dwelling or place of residence associated with another entity.
- 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_69d81c639e808190a0e4b4f3d31c6a59 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de2eb22e388190904fc87765176c91 |
completed | April 14, 2026, 12:10 p.m. |
| PD | Predicate disambiguation | batch_69dd465dfbc4819090d8c61fd572d35f |
completed | April 13, 2026, 7:39 p.m. |
Created at: April 9, 2026, 10:18 p.m.