Triple
T2440013
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | National Memorial for Peace and Justice |
E53250
|
entity |
| Predicate | numberOfMonuments |
P32446
|
FINISHED |
| Object | over 800 |
—
|
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: over 800 | Statement: [National Memorial for Peace and Justice, numberOfMonuments, over 800]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfMonuments Context triple: [National Memorial for Peace and Justice, numberOfMonuments, over 800]
-
A.
hasNumberOfMonuments
chosen
Indicates the specific count of monuments associated with or present in a given entity.
-
B.
monumentSubject
Indicates that the subject serves as the monument or commemorative structure associated with another entity.
-
C.
significantMonument
Indicates that something is a monument of notable historical, cultural, or symbolic importance.
-
D.
builtMonument
Indicates that one entity constructed or created a monument in honor of, or related to, another entity.
-
E.
resultForMonument
Indicates that something (such as data, analysis, or an outcome) is the result specifically associated with a given monument.
- 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_69ab495b6dac8190ac82661aa1452222 |
completed | March 6, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69abcebf7cac8190889e6890d72c256c |
completed | March 7, 2026, 7:07 a.m. |
| PD | Predicate disambiguation | batch_69abc5ac11b081908ce6a506e81a742a |
completed | March 7, 2026, 6:29 a.m. |
Created at: March 6, 2026, 9:43 p.m.