Triple
T1730655
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Senate of Liberia |
E37801
|
entity |
| Predicate | membersPerCounty |
P27148
|
FINISHED |
| Object | 2 |
—
|
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: 2 | Statement: [Senate of Liberia, membersPerCounty, 2]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: membersPerCounty Context triple: [Senate of Liberia, membersPerCounty, 2]
-
A.
populationRankInCounty
Indicates the relative position of an entity in terms of population size compared to other entities within the same county.
-
B.
hasNumberOfCounties
chosen
Indicates the relationship that specifies how many counties are associated with or contained within a given entity.
-
C.
inCounty
Indicates that one entity is geographically or administratively located within the boundaries of a specified county.
-
D.
includesCounty
Indicates that a larger geographic or administrative region contains or encompasses a specific county within its boundaries.
-
E.
mostPopulousCountyIn
Indicates that the subject is the county with the largest population within the specified object region or jurisdiction.
- 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_69a8861cc6ac8190ac0b2e31ccf62851 |
completed | March 4, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69ab5c553e508190b0f511b05e07fa20 |
completed | March 6, 2026, 10:59 p.m. |
| PD | Predicate disambiguation | batch_69aa61c25a648190892de94c997fb983 |
completed | March 6, 2026, 5:10 a.m. |
Created at: March 4, 2026, 7:30 p.m.