Triple
T3892122
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sedefkar Mehmed Agha |
E88084
|
entity |
| Predicate | hasPartInCareer |
P19243
|
FINISHED |
| Object | imperial building projects in Istanbul |
—
|
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: imperial building projects in Istanbul | Statement: [Sedefkar Mehmed Agha, hasPartInCareer, imperial building projects in Istanbul]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPartInCareer Context triple: [Sedefkar Mehmed Agha, hasPartInCareer, imperial building projects in Istanbul]
-
A.
partOfCareer
chosen
Indicates that one entity represents a role, position, or period that forms a component or phase within another entity’s overall career.
-
B.
hasCareerTrack
Indicates that an entity is associated with or follows a particular career path or professional progression.
-
C.
hasWorkedIn
Indicates that a person has been employed or has performed work within a particular organization, location, or domain for some period of time.
-
D.
spentEntireCareerWith
Indicates that an individual has worked exclusively for a single organization or team for the full duration of their professional career.
-
E.
workedAs
Indicates that an entity held a particular job, role, or position, performing work in that capacity.
- 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_69aed9466d548190939f5217a23ed4ac |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aef1abe2dc81909c18aeae9b286898 |
completed | March 9, 2026, 4:13 p.m. |
| PD | Predicate disambiguation | batch_69aee75b5b808190a348a31b1325d3d0 |
completed | March 9, 2026, 3:29 p.m. |
Created at: March 9, 2026, 3:21 p.m.