Triple
T4471625
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Martians |
E98506
|
entity |
| Predicate | settingOfConflict |
P56733
|
FINISHED |
| Object | late 19th-century England |
—
|
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: late 19th-century England | Statement: [Martians, settingOfConflict, late 19th-century England]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: settingOfConflict Context triple: [Martians, settingOfConflict, late 19th-century England]
-
A.
conflictSpecific
Indicates a specific, concrete instance or type of conflict that exists between the related entities.
-
B.
conflictIn
Indicates that one entity is involved in, associated with, or occurs within a particular conflict or dispute.
-
C.
conflictType
Indicates the specific kind or category of conflict that characterizes the relationship or interaction between entities.
-
D.
conflictBelligerent
Indicates that an entity is a participating belligerent (e.g., a country, group, or force) in a specific conflict.
-
E.
conflictStance
Indicates a party’s position, attitude, or alignment regarding a particular conflict or dispute.
- 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_69b3454b4ae481908967426dd37284d6 |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b356fb69a0819099f0005779f4fcac |
completed | March 13, 2026, 12:14 a.m. |
| PD | Predicate disambiguation | batch_69b3563bf4f8819081726cde3a34460b |
completed | March 13, 2026, 12:11 a.m. |
| PDg | Predicate description generation | batch_69b356f9afc48190acb50c45a310e072 |
completed | March 13, 2026, 12:14 a.m. |
Created at: March 12, 2026, 11:35 p.m.