Triple
T19044596
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Flannan Isles Lighthouse |
E466097
|
entity |
| Predicate | keeperDisappearanceNumberOfMen |
P87238
|
FINISHED |
| Object | 3 |
—
|
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: 3 | Statement: [Flannan Isles Lighthouse, keeperDisappearanceNumberOfMen, 3]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: keeperDisappearanceNumberOfMen Context triple: [Flannan Isles Lighthouse, keeperDisappearanceNumberOfMen, 3]
-
A.
missingPersonsEstimate
chosen
Indicates an estimated number of people who are unaccounted for or reported missing in a given context or event.
-
B.
placeOfDisappearance
Indicates the location where an entity was last seen or went missing.
-
C.
timeOfDisappearance
Indicates the specific time at which an entity disappeared or was last observed to no longer be present.
-
D.
yearOfDisappearance
Indicates the specific year in which an entity disappeared or ceased to be present.
-
E.
numberOfNamesOnWallOfMissing
Indicates the count of individual names that appear on a designated wall listing missing persons.
- 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_69d8dd0359648190bc2a9202c5cf29d2 |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5d803b2b08190b057d4b5bc555d4f |
completed | April 20, 2026, 7:38 a.m. |
| PD | Predicate disambiguation | batch_69e4b99633c8819097988608c278ecf8 |
completed | April 19, 2026, 11:16 a.m. |
Created at: April 10, 2026, 12:03 p.m.