Triple
T16130628
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Franklin Avenue Station |
E391385
|
entity |
| Predicate | servesNeighborhoodType |
P68386
|
FINISHED |
| Object | residential neighborhoods |
—
|
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: residential neighborhoods | Statement: [Franklin Avenue Station, servesNeighborhoodType, residential neighborhoods]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: servesNeighborhoodType Context triple: [Franklin Avenue Station, servesNeighborhoodType, residential neighborhoods]
-
A.
areaServedType
chosen
Indicates the type or category of area that is served by an entity or service.
-
B.
servedNearbyEstates
Indicates that an entity provided services or assistance to estates located in its immediate geographic vicinity.
-
C.
notableNeighborhoodType
Indicates that a neighborhood is notably characterized by, or strongly associated with, a particular type or category (e.g., residential, commercial, historic).
-
D.
servesNearbyCommunities
Indicates that an entity provides services or support to communities located in its surrounding area.
-
E.
cityServedType
Indicates the type or category of city that is served by a given entity (such as a facility, service, or infrastructure).
- 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_69d87f1bb0988190b490d273dbf3fd03 |
completed | April 10, 2026, 4:39 a.m. |
| NER | Named-entity recognition | batch_69e2020829e88190b51ab32d22cf0259 |
completed | April 17, 2026, 9:48 a.m. |
| PD | Predicate disambiguation | batch_69e1828518c48190a8ef3aaa46a1f639 |
completed | April 17, 2026, 12:44 a.m. |
Created at: April 10, 2026, 5:01 a.m.