Triple
T13790360
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Christ Church in the City of Boston |
E331377
|
entity |
| Predicate | towerUsedFor |
P39918
|
FINISHED |
| Object | lantern signals |
—
|
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: lantern signals | Statement: [Christ Church in the City of Boston, towerUsedFor, lantern signals]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: towerUsedFor Context triple: [Christ Church in the City of Boston, towerUsedFor, lantern signals]
-
A.
towerPurpose
chosen
Indicates the primary function or intended use that a tower is designed or employed to serve.
-
B.
towerLocation
Indicates that a tower is located at, or associated with, a specific place or geographic location.
-
C.
towerType
Indicates the specific kind or classification of a tower that an entity is associated with or represents.
-
D.
buildingUsedBy
Indicates that a particular building is utilized or occupied by a specified entity for some purpose.
-
E.
towerAttachment
Indicates that one entity is physically attached to or structurally connected with a tower.
- 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_69d81c58feb08190a77bca8bf7d6d20f |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de024af32c8190a9bd1278e09564ba |
completed | April 14, 2026, 9 a.m. |
| PD | Predicate disambiguation | batch_69dbc85fb600819098a2aab48169be96 |
completed | April 12, 2026, 4:29 p.m. |
Created at: April 9, 2026, 10:11 p.m.