Triple
T29898723
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mr. Eko |
E759349
|
entity |
| Predicate | aircraftCrashSurvivorOf |
P162692
|
FINISHED |
| Object | Oceanic Flight 815 |
—
|
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: Oceanic Flight 815 | Statement: [Mr. Eko, aircraftCrashSurvivorOf, Oceanic Flight 815]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: aircraftCrashSurvivorOf Context triple: [Mr. Eko, aircraftCrashSurvivorOf, Oceanic Flight 815]
-
A.
survivedAccident
chosen
Indicates that an entity continued to live or remain unharmed after being involved in an accident.
-
B.
survivingAircraftCount
Indicates the number of aircraft that remain operational or intact after a specified event, condition, or time period.
-
C.
survivingAircraftLocation
Indicates the location where an aircraft that has survived an incident or event is situated.
-
D.
survivesShipwreck
Indicates that an entity continues to live or remain alive after experiencing a shipwreck.
-
E.
survivorsJourney
Indicates the ongoing process or path a survivor takes as they cope with, adapt to, and move forward from a traumatic or life-threatening experience.
- 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_69f2245f1cf88190978c70d1a1d2cb73 |
completed | April 29, 2026, 3:31 p.m. |
| NER | Named-entity recognition | batch_69f6a916d2e08190bafc01cba73b6469 |
completed | May 3, 2026, 1:47 a.m. |
| PD | Predicate disambiguation | batch_69f6a7548eb48190a69b60a3c6ad53b9 |
completed | May 3, 2026, 1:39 a.m. |
Created at: April 29, 2026, 6:05 p.m.