Triple
T14192839
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kathiri State of Seiyun |
E351754
|
entity |
| Predicate | joinedFederationOfSouthArabia |
P113157
|
FINISHED |
| Object | 1960s |
—
|
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: 1960s | Statement: [Kathiri State of Seiyun, joinedFederationOfSouthArabia, 1960s]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: joinedFederationOfSouthArabia Context triple: [Kathiri State of Seiyun, joinedFederationOfSouthArabia, 1960s]
-
A.
joinedArabLeague
Indicates that an entity became a member state of the Arab League.
-
B.
joinedFederalRepublic
Indicates that an entity became a member of, or was incorporated into, a federal republic.
-
C.
establishedThirdSaudiState
Indicates that an entity founded or brought into existence the Third Saudi State (the modern Kingdom of Saudi Arabia).
-
D.
establishedSecondSaudiState
Indicates that an entity played a key role in founding or creating the Second Saudi State.
-
E.
joinedFrance
Indicates that an entity became a member of or was incorporated into France.
- 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_69d827894ac0819097803e57f3227b23 |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de61e0a52081908213aa6e548d4418 |
completed | April 14, 2026, 3:48 p.m. |
| PD | Predicate disambiguation | batch_69de05baed64819096590e5618a3a8ed |
completed | April 14, 2026, 9:15 a.m. |
| PDg | Predicate description generation | batch_69de239a02e881909b0e2679487e4ab2 |
completed | April 14, 2026, 11:23 a.m. |
Created at: April 10, 2026, 1:04 a.m.