Triple
T4541976
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Manila American Cemetery |
E107553
|
entity |
| Predicate | hasTypeOfMemorialization |
P7960
|
FINISHED |
| Object | names on walls of the missing |
—
|
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: names on walls of the missing | Statement: [Manila American Cemetery, hasTypeOfMemorialization, names on walls of the missing]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTypeOfMemorialization Context triple: [Manila American Cemetery, hasTypeOfMemorialization, names on walls of the missing]
-
A.
memorialType
chosen
Indicates the specific kind or category of memorial associated with an entity (e.g., plaque, statue, monument).
-
B.
hasMemorial
Indicates that a memorial exists in honor of, or dedicated to, a particular entity.
-
C.
monumentType
Indicates the specific kind or category of monument that an entity is classified as.
-
D.
hasArtOrMemorial
Indicates that one entity possesses, contains, or is associated with a work of art or a memorial related to another entity.
-
E.
hasTypeOfPersonCommemorated
Indicates that something is associated with or dedicated to a person of a specified type or role being commemorated.
- 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_69bd43f922788190b7edfa294e39b178 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd57d219d88190a67ada845323d7fb |
completed | March 20, 2026, 2:21 p.m. |
| PD | Predicate disambiguation | batch_69bd5220e40481908ca2d7e2c43d8531 |
completed | March 20, 2026, 1:56 p.m. |
Created at: March 20, 2026, 1:04 p.m.