Triple
T11056876
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Harriet Tubman |
E261398
|
entity |
| Predicate | roleInUndergroundRailroad |
P95715
|
FINISHED |
| Object | conductor |
—
|
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: conductor | Statement: [Harriet Tubman, roleInUndergroundRailroad, conductor]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: roleInUndergroundRailroad Context triple: [Harriet Tubman, roleInUndergroundRailroad, conductor]
-
A.
roleInBulletTrain
Indicates the specific function, position, or responsibility an entity has within the context of a bullet train system or operation.
-
B.
roleInTrain
chosen
Indicates the specific function or position an entity holds within the context of a train (e.g., passenger, conductor, locomotive, or car type).
-
C.
roleInFruitvaleStation
Indicates that an entity had a specific role or involvement in the film "Fruitvale Station."
-
D.
roleInHolocaust
Indicates that an entity had a specific involvement, function, or participation in events or activities related to the Holocaust.
-
E.
roleInExpedition
Indicates the specific function, duty, or position an entity holds within the context of a particular expedition.
- 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_69d6aa98650481908609c7c56bfa7902 |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d798a2404c819090cb0825a67a64fa |
completed | April 9, 2026, 12:16 p.m. |
| PD | Predicate disambiguation | batch_69d7440da46c8190a77380d5d747ac9c |
completed | April 9, 2026, 6:15 a.m. |
Created at: April 8, 2026, 9:26 p.m.