Triple
T15154978
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lehi Museum in Tel Aviv |
E362045
|
entity |
| Predicate | hasMemorialRoom |
P117538
|
FINISHED |
| Object | room where Avraham Stern was killed |
—
|
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: room where Avraham Stern was killed | Statement: [Lehi Museum in Tel Aviv, hasMemorialRoom, room where Avraham Stern was killed]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMemorialRoom Context triple: [Lehi Museum in Tel Aviv, hasMemorialRoom, room where Avraham Stern was killed]
-
A.
hasMemorial
Indicates that a memorial exists in honor of, or dedicated to, a particular entity.
-
B.
hasAdjacentMemorial
Indicates that one memorial is located directly next to or in close proximity to another memorial.
-
C.
hasMemorialContext
Indicates that something is related to, associated with, or situated within the context of a memorial or commemorative setting.
-
D.
hasMemorialMuseum
Indicates that a memorial museum is dedicated to, associated with, or established in honor of a particular entity.
-
E.
hasMemorialPractice
Indicates that an entity engages in or is associated with a particular practice, ritual, or activity intended to commemorate or remember someone or something.
- 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_69d85a0759908190b8a051d2e2a1cbe6 |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e0060b0cd08190afad14cffcc7d93f |
completed | April 15, 2026, 9:41 p.m. |
| PD | Predicate disambiguation | batch_69deb9779acc81908ed2dad382c42dca |
completed | April 14, 2026, 10:02 p.m. |
| PDg | Predicate description generation | batch_69dec71e8dcc81908badc834b6ccf273 |
completed | April 14, 2026, 11 p.m. |
Created at: April 10, 2026, 3:08 a.m.