Triple
T18215476
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Little Village Arch |
E436142
|
entity |
| Predicate | nicknameOfNeighborhoodItMarks |
P130276
|
FINISHED |
| Object | Mexican capital of the Midwest |
—
|
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: Mexican capital of the Midwest | Statement: [Little Village Arch, nicknameOfNeighborhoodItMarks, Mexican capital of the Midwest]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: nicknameOfNeighborhoodItMarks Context triple: [Little Village Arch, nicknameOfNeighborhoodItMarks, Mexican capital of the Midwest]
-
A.
hasNeighbourhood
Indicates that one entity is located within, or is associated with, a particular neighborhood area of another entity.
-
B.
headquartersNeighborhood
Indicates that an organization’s main headquarters is located within a specific neighborhood.
-
C.
neighborhood
Indicates that one entity is located in close spatial proximity to another, typically within the same local area or district.
-
D.
partOfNeighborhoodNetwork
Indicates that an entity belongs to, or is included within, a specific neighborhood’s interconnected network or system.
-
E.
hasStreetNickname
Indicates that an entity is known by a particular informal or colloquial name used on the street or in everyday speech.
- 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_69d8b9103a8081908bbb0836fef10efd |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4e476a6548190bda03190c5f531ad |
completed | April 19, 2026, 2:19 p.m. |
| PD | Predicate disambiguation | batch_69e4332155d88190b106d0dceb4554af |
completed | April 19, 2026, 1:42 a.m. |
| PDg | Predicate description generation | batch_69e438f684e48190b38c64b58c518b6a |
completed | April 19, 2026, 2:07 a.m. |
Created at: April 10, 2026, 10:32 a.m.