Triple
T38174
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Independence Hall |
E756
|
entity |
| Predicate | hasBellTower |
P2495
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Independence Hall, hasBellTower, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasBellTower Context triple: [Independence Hall, hasBellTower, true]
-
A.
hasCityHall
Indicates that a location or administrative area possesses or is served by a specific city hall building or institution.
-
B.
hasStatue
Indicates that one entity possesses, contains, or is associated with a statue representing or located within it.
-
C.
hasStationBuilding
Indicates that a station is associated with or includes a station building as part of its facilities.
-
D.
hasTown
Indicates that one entity possesses, contains, or is associated with a town as part of its structure, jurisdiction, or composition.
-
E.
hasEntranceOn
Indicates that one entity’s entrance or access point is located on or faces a specified side, boundary, or feature of another entity.
- 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_69a247a8f6c08190bac804906d62ed5a |
completed | Feb. 28, 2026, 1:40 a.m. |
| NER | Named-entity recognition | batch_69a24b4d5bd08190a3a48eb26e67768c |
completed | Feb. 28, 2026, 1:56 a.m. |
| PD | Predicate disambiguation | batch_69a24ab6141881908701106aa97e4735 |
completed | Feb. 28, 2026, 1:53 a.m. |
| PDg | Predicate description generation | batch_69a24b4c59b08190854b5335f5eff790 |
completed | Feb. 28, 2026, 1:56 a.m. |
Created at: Feb. 28, 2026, 1:46 a.m.