Triple
T35355546
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | East Taylor Street |
E1021312
|
entity |
| Predicate | hasCitySquareAlong |
P149894
|
FINISHED |
| Object | Lafayette Square |
—
|
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: Lafayette Square | Statement: [East Taylor Street, hasCitySquareAlong, Lafayette Square]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCitySquareAlong Context triple: [East Taylor Street, hasCitySquareAlong, Lafayette Square]
-
A.
hasFamousSquare
chosen
Indicates that a place possesses or contains a well-known public square associated with it.
-
B.
hasMonumentInCenter
Indicates that a place or area has a monument located at its central point or main focal area.
-
C.
capitalCitySquareOf
Indicates that one entity is a public square located in or associated with the capital city of the other entity.
-
D.
hasPublicSquareInFront
Indicates that a building or structure has a public square located directly in front of it.
-
E.
usesCathedralSquare
Indicates that an entity makes use of or operates within a specific cathedral square as a functional or contextual location.
- 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_69f76def44c881908a20e8008572eb44 |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69fb3425666081908916fcbf3b5dd907 |
completed | May 6, 2026, 12:29 p.m. |
| PD | Predicate disambiguation | batch_69fb2f5f3164819099429c2cc3d24e01 |
completed | May 6, 2026, 12:09 p.m. |
Created at: May 3, 2026, 4:03 p.m.