Triple
T38422618
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | For the Fallen |
E903270
|
entity |
| Predicate | hasOdeOfRemembranceStanza |
P190863
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [For the Fallen, hasOdeOfRemembranceStanza, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasOdeOfRemembranceStanza Context triple: [For the Fallen, hasOdeOfRemembranceStanza, true]
-
A.
hasMemorial
Indicates that a memorial exists in honor of, or dedicated to, a particular entity.
-
B.
appearsInMemoryOf
Indicates that one entity is present or recalled within another entity’s memory or recollection.
-
C.
hasCanonicalPoem
Indicates that an entity is associated with a poem recognized as its standard or authoritative version.
-
D.
hasMemorialElements
Indicates that something includes or incorporates components that serve as a memorial or commemoration of someone or something.
-
E.
hasMemorialContext
Indicates that something is related to, associated with, or situated within the context of a memorial or commemorative setting.
- 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_69f76e67e4fc8190a7d08dfe9a8af998 |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_69fcd1499e2c81909bafd84dc4810f45 |
completed | May 7, 2026, 5:52 p.m. |
| PD | Predicate disambiguation | batch_69fcccf024ec819086383ffbb6cfc036 |
completed | May 7, 2026, 5:33 p.m. |
| PDg | Predicate description generation | batch_69fcd148e6d4819082c118832ecc599b |
completed | May 7, 2026, 5:52 p.m. |
Created at: May 3, 2026, 4:31 p.m.