Triple
T28654214
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Moses Blah |
E725283
|
entity |
| Predicate | tookOfficeDuring |
P165179
|
FINISHED |
| Object | Second Liberian Civil War |
—
|
NE NERFINISHED |
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: Second Liberian Civil War | Statement: [Moses Blah, tookOfficeDuring, Second Liberian Civil War]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: tookOfficeDuring Context triple: [Moses Blah, tookOfficeDuring, Second Liberian Civil War]
-
A.
termOfOfficeInaugurated
Indicates the event or date on which an individual officially begins their term of office through an inauguration.
-
B.
succeededToOfficeIn
Indicates that one entity assumed or took over an office or position previously held by another entity at a specified time or in a specified succession.
-
C.
timeInOfficeBeginsIn
Indicates the point in time or date when an entity’s term, tenure, or period in office starts.
-
D.
cameToPowerIn
Indicates the time or context in which an entity assumed control, authority, or leadership over a group, organization, or territory.
-
E.
beganDuringPresidencyOf
Indicates that an event, process, or state started while a specified person was serving as president.
- 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_69f01d84f5f0819087ab5e6143b14ed7 |
completed | April 28, 2026, 2:37 a.m. |
| NER | Named-entity recognition | batch_69f65705a3048190a3728b695ba2ae65 |
completed | May 2, 2026, 7:56 p.m. |
| PD | Predicate disambiguation | batch_69f651ac855481908e30c3b345d31356 |
completed | May 2, 2026, 7:34 p.m. |
| PDg | Predicate description generation | batch_69f6562ef4e4819082ce6abd41b74dc5 |
completed | May 2, 2026, 7:53 p.m. |
Created at: April 28, 2026, 4:54 a.m.