Triple
T3974675
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Walter Schloss |
E85610
|
entity |
| Predicate | preferredMetric |
P1459
|
FINISHED |
| Object | low price-to-book ratio |
—
|
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: low price-to-book ratio | Statement: [Walter Schloss, preferredMetric, low price-to-book ratio]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: preferredMetric Context triple: [Walter Schloss, preferredMetric, low price-to-book ratio]
-
A.
usesMetric
chosen
Indicates that one entity adopts, applies, or relies on a particular metric or measurement standard in its operation, evaluation, or description.
-
B.
primaryMetric
Indicates the main quantitative measure used to evaluate the performance, success, or impact of an entity or process relative to its goals.
-
C.
isMetric
Indicates that something satisfies the properties required to be considered a metric, such as defining distances that obey non-negativity, identity, symmetry, and the triangle inequality.
-
D.
unitPreference
Indicates a relationship where one entity specifies or favors a particular unit of measurement or representation over others.
-
E.
secondaryMetric
Indicates that one metric serves as an additional, supporting measure used alongside a primary metric for evaluation or analysis.
- 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_69aed93908348190a26c8aaf4fab3e86 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aefaca33e4819091957c7915857a42 |
completed | March 9, 2026, 4:52 p.m. |
| PD | Predicate disambiguation | batch_69aef8f252b081909749d40440d372b2 |
completed | March 9, 2026, 4:44 p.m. |
Created at: March 9, 2026, 3:32 p.m.