Triple
T17031189
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Makani Harrelson |
E413197
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Makani |
E697131
|
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: Makani | Statement: [Makani Harrelson, givenName, Makani]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Makani Context triple: [Makani Harrelson, givenName, Makani]
-
A.
Makani
chosen
Makani was an experimental Alphabet X (formerly Google X) project that developed airborne wind turbines using tethered kites to generate renewable energy.
-
B.
Mawani
Mawani is Saudi Arabia’s national ports authority, responsible for overseeing, regulating, and developing the country’s seaport infrastructure and operations.
-
C.
Manihi
Manihi is a remote coral atoll in French Polynesia’s Tuamotu Archipelago, known for its tranquil lagoon, traditional pearl farming, and unspoiled island scenery.
-
D.
Kayamandi
Kayamandi is a predominantly Black township on the outskirts of Stellenbosch in South Africa, known for its vibrant community life and history rooted in apartheid-era urban planning.
-
E.
Makuna
Makuna is an indigenous Tucanoan language spoken by the Makuna people of the northwest Amazon region, primarily in Colombia and Brazil.
- 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_69d886cd18288190b006abab23f811b7 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3d5d9e7d481909d3d5bd241bd68f1 |
completed | April 18, 2026, 7:04 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a011b5748bc8190832737a70219e7a1 |
completed | May 10, 2026, 11:57 p.m. |
Created at: April 10, 2026, 5:33 a.m.