Triple
T384788
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Panic of 1893 |
E8756
|
entity |
| Predicate | mainVictim |
P699
|
FINISHED |
| Object | railroad industry in the United States |
—
|
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: railroad industry in the United States | Statement: [Panic of 1893, mainVictim, railroad industry in the United States]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: mainVictim Context triple: [Panic of 1893, mainVictim, railroad industry in the United States]
-
A.
notableVictim
Indicates that the subject is a person or entity who is notably recognized as a victim of the object (such as an event, crime, or harmful action).
-
B.
portraysAsVictim
Indicates that one entity represents or depicts another entity as a victim in a given context or narrative.
-
C.
victimGroup
chosen
Indicates that one group or entity is the target or recipient of harm, abuse, or wrongdoing caused by another.
-
D.
mainProtagonist
Indicates that the subject is the central character or primary focus in the narrative of the related work.
-
E.
mainAttacker
Indicates that an entity is the primary or leading aggressor responsible for initiating or carrying out an attack against another entity.
- 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_69a2e7f47dd08190a4e294ccbbe46cd4 |
completed | Feb. 28, 2026, 1:04 p.m. |
| NER | Named-entity recognition | batch_69a2ec4345a48190a413261cba4eafd7 |
completed | Feb. 28, 2026, 1:23 p.m. |
| PD | Predicate disambiguation | batch_69a2e967d84c8190a6b647f78d95d4e4 |
completed | Feb. 28, 2026, 1:11 p.m. |
Created at: Feb. 28, 2026, 1:08 p.m.