Triple
T30539160
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Qiddiya Investment Company |
E777226
|
entity |
| Predicate | roleInQiddiya |
P45817
|
FINISHED |
| Object | master planner |
—
|
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: master planner | Statement: [Qiddiya Investment Company, roleInQiddiya, master planner]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: roleInQiddiya Context triple: [Qiddiya Investment Company, roleInQiddiya, master planner]
-
A.
roleInArabia
Indicates that an entity holds or held a specific role, position, or function within the context of Arabia.
-
B.
roleInMecca
Indicates that an entity holds or performs a specific role, function, or position in the context of Mecca.
-
C.
roleInKairouan
Indicates that an entity holds or held a specific role, position, or function in relation to Kairouan.
-
D.
roleInMedina
Indicates the specific function, position, or responsibility an entity holds within the context of Medina.
-
E.
roleInAttraction
chosen
Indicates the specific function or position an entity holds within the context of a particular attraction or point of interest.
- 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_69f2249d183c8190b79937c1768d2163 |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69ff6ef0d61c81909162d37c15a1a3c3 |
completed | May 9, 2026, 5:29 p.m. |
| PD | Predicate disambiguation | batch_69ff6c6a58e08190921317062cd9d489 |
completed | May 9, 2026, 5:18 p.m. |
Created at: April 29, 2026, 8:19 p.m.