Triple
T35511063
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Railroad (Fallout 4) |
E1026285
|
entity |
| Predicate | relationshipWithMinutemen |
P207017
|
FINISHED |
| Object | can ally in some endings |
—
|
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: can ally in some endings | Statement: [Railroad (Fallout 4), relationshipWithMinutemen, can ally in some endings]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipWithMinutemen Context triple: [Railroad (Fallout 4), relationshipWithMinutemen, can ally in some endings]
-
A.
roleInBattleOfBennington
Indicates the specific role or involvement an entity had in the Battle of Bennington.
-
B.
roleInAmericanRevolution
Indicates that an entity had a specific role, position, or involvement in events or activities related to the American Revolution.
-
C.
associatedWithMilitaryHistory
Indicates a relationship in which something is connected or relevant to military history, such as events, figures, institutions, or artifacts.
-
D.
PatriotCasualties
Indicates that the event involves casualties suffered by patriot forces or supporters.
-
E.
roleInBostonMassacre
Indicates that an entity had a specific role or involvement in the historical event known as the Boston Massacre.
- 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_69f76dfd61208190b93ec6dc439cab41 |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_6a037c92f03c8190ae2751270b195423 |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a037a04d8348190a4819666eab42c9b |
completed | May 12, 2026, 7:05 p.m. |
| PDg | Predicate description generation | batch_6a037c82179081908325a59b8539b3a8 |
completed | May 12, 2026, 7:16 p.m. |
Created at: May 3, 2026, 4:04 p.m.