Triple
T2253103
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hassan Tower |
E49659
|
entity |
| Predicate | originalIntendedStatus |
P36739
|
FINISHED |
| Object | minaret of the world’s largest mosque |
—
|
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: minaret of the world’s largest mosque | Statement: [Hassan Tower, originalIntendedStatus, minaret of the world’s largest mosque]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: originalIntendedStatus Context triple: [Hassan Tower, originalIntendedStatus, minaret of the world’s largest mosque]
-
A.
originalTextStatus
Indicates the relationship between a text and its current state or condition relative to its original, unmodified form.
-
B.
primaryStatus
Indicates the main or most important status assigned to an entity among potentially multiple statuses.
-
C.
originalDestination
Indicates the initial or intended destination associated with an entity before any changes, rerouting, or redirection occur.
-
D.
earlierStatus
Indicates that one status or condition occurred or was valid before another status in time.
-
E.
canonicalStatus
Indicates the formal or official standing of an entity within an established authoritative or normative system.
- 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_69a88aaa9250819095e127d0d77e8a32 |
completed | March 4, 2026, 7:40 p.m. |
| NER | Named-entity recognition | batch_69abc11eb2708190bc5a3d152a3bb133 |
completed | March 7, 2026, 6:09 a.m. |
| PD | Predicate disambiguation | batch_69abbdb34c148190b51e99f540f97204 |
completed | March 7, 2026, 5:54 a.m. |
| PDg | Predicate description generation | batch_69abbe86dbcc81908c72793af8fe2a4d |
completed | March 7, 2026, 5:58 a.m. |
Created at: March 4, 2026, 7:47 p.m.