Triple
T7696122
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ka Felix |
E174373
|
entity |
| Predicate | linkedToPosition |
P36701
|
FINISHED |
| Object | first Executive Minister of Iglesia ni Cristo |
—
|
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: first Executive Minister of Iglesia ni Cristo | Statement: [Ka Felix, linkedToPosition, first Executive Minister of Iglesia ni Cristo]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: linkedToPosition Context triple: [Ka Felix, linkedToPosition, first Executive Minister of Iglesia ni Cristo]
-
A.
linkedPosition
Indicates that one position is associated or connected to another position in a defined way.
-
B.
refersToPosition
chosen
Indicates that one entity makes reference to, or is associated with, a specific position or location of another entity.
-
C.
linkedLocation
Indicates that one location is associated or connected to another location in a meaningful way, such as being related, referenced, or contextually tied.
-
D.
linkedToRegion
Indicates that one entity is associated or connected to a specific geographic or administrative region.
-
E.
linkedByStructure
Indicates that two entities are connected or associated through a shared structural element, configuration, or framework.
- 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_69c6995966348190939e6c37ba272c06 |
completed | March 27, 2026, 2:51 p.m. |
| NER | Named-entity recognition | batch_69c706d1f0208190bc5b695aa5736244 |
completed | March 27, 2026, 10:38 p.m. |
| PD | Predicate disambiguation | batch_69c70163dea88190ae729df50e63dfd7 |
completed | March 27, 2026, 10:15 p.m. |
Created at: March 27, 2026, 4:03 p.m.