Triple
T451957
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | President of Pakistan |
E7148
|
entity |
| Predicate | sitsAtop |
P13359
|
FINISHED |
| Object | executive branch of Pakistan in a ceremonial capacity |
—
|
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: executive branch of Pakistan in a ceremonial capacity | Statement: [President of Pakistan, sitsAtop, executive branch of Pakistan in a ceremonial capacity]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: sitsAtop Context triple: [President of Pakistan, sitsAtop, executive branch of Pakistan in a ceremonial capacity]
-
A.
isToppedWith
Indicates that one entity serves as a topping placed on the surface of another entity.
-
B.
isAt
Indicates that one entity is located at or present in the place or position of another entity.
-
C.
seatOnBody
Indicates that one entity functions as a seat or seating surface that is physically attached or integrated to a body or body-like structure.
-
D.
hasScenicViewOf
Indicates that one entity offers a visually appealing or picturesque view of another entity.
-
E.
imposedOn
Indicates that one party enforces, applies, or places a requirement, burden, or constraint onto another party or 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_69a2e7e4676c81909ea0dbdecac0687c |
completed | Feb. 28, 2026, 1:04 p.m. |
| NER | Named-entity recognition | batch_69a2ef854f7481909dc2207faf0327ec |
completed | Feb. 28, 2026, 1:37 p.m. |
| PD | Predicate disambiguation | batch_69a2ede3187c8190a7ced078f0ec3476 |
completed | Feb. 28, 2026, 1:30 p.m. |
| PDg | Predicate description generation | batch_69a2eeba8a488190986cc7381332f783 |
completed | Feb. 28, 2026, 1:33 p.m. |
Created at: Feb. 28, 2026, 1:12 p.m.