Triple
T1421474
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Renaissance Tower |
E30233
|
entity |
| Predicate | yearRenovated |
P27501
|
FINISHED |
| Object | 1986 |
—
|
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: 1986 | Statement: [Renaissance Tower, yearRenovated, 1986]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: yearRenovated Context triple: [Renaissance Tower, yearRenovated, 1986]
-
A.
renovationYear
chosen
Indicates the year in which an entity underwent renovation or significant refurbishment.
-
B.
yearBuilt
Indicates the specific year in which something (typically a structure or object) was constructed or completed.
-
C.
renovatedFrom
Indicates that one entity has been updated, improved, or restored by modifying or reworking an earlier version represented by another entity.
-
D.
renovatedBy
Indicates that an entity has been improved, restored, or updated through renovation work performed by another entity.
-
E.
reconstructionYear
Indicates the year in which something was rebuilt, restored, or reconstructed after damage, alteration, or destruction.
- 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_69a498fb823c8190a67ce4c4837e641a |
completed | March 1, 2026, 7:52 p.m. |
| NER | Named-entity recognition | batch_69a4c52e4ed881908d85e0cb9fe851ac |
completed | March 1, 2026, 11:01 p.m. |
| PD | Predicate disambiguation | batch_69a4c4752abc8190a33b634c4d6fad28 |
completed | March 1, 2026, 10:57 p.m. |
Created at: March 1, 2026, 8 p.m.