Triple
T6675764
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | South Tarawa |
E151847
|
entity |
| Predicate | hasPart |
P35
|
FINISHED |
| Object | Eita |
E349072
|
NE 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: Eita | Statement: [South Tarawa, hasPart, Eita]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Eita Context triple: [South Tarawa, hasPart, Eita]
-
A.
Eita
chosen
Eita is a village located on Tarawa Atoll in the Pacific island nation of Kiribati.
-
B.
Ese Ejja
The Ese Ejja are an indigenous people of the Amazon Basin, traditionally living along rivers in southeastern Peru and northern Bolivia, known for their fishing-based livelihood and distinct language and culture.
-
C.
Toinette
Toinette is the sharp-witted, outspoken maid in Molière’s comedy "Le Malade imaginaire," known for her clever schemes and satirical commentary on her hypochondriac master.
-
D.
Ela
Ela is a feminine given name used in various cultures, often as a short form of names like Eleanor or Elżbieta.
-
E.
Otra
Otra is a major river in southern Norway that flows through the Agder region to the city of Kristiansand before emptying into the Skagerrak.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69c687f830bc81909eb8b04dbb8450b1 |
completed | March 27, 2026, 1:36 p.m. |
| NER | Named-entity recognition | batch_69c6b0f3021481908c2599349eb6ea07 |
completed | March 27, 2026, 4:31 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c6f7a30b7481908c36ff9035f62731 |
completed | March 27, 2026, 9:33 p.m. |
Created at: March 27, 2026, 2:03 p.m.